Ancestry Script (DFP-Study)
Ezekiel Wamble
2024-11-15
install packages:
library(plyr)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:plyr':
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## arrange, count, desc, failwith, id, mutate, rename, summarise,
## summarize## The following objects are masked from 'package:stats':
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## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(tidyr)
library(readxl)
library("rstatix")##
## Attaching package: 'rstatix'## The following objects are masked from 'package:plyr':
##
## desc, mutate## The following object is masked from 'package:stats':
##
## filterlibrary("ggplot2")
library("dplyr")
library("ggpubr")##
## Attaching package: 'ggpubr'## The following object is masked from 'package:plyr':
##
## mutatelibrary("dunn.test")
library("ARTool")
library(openxlsx)
library("rio")
library(corrplot)## corrplot 0.95 loadedlocate file:
DFPMasterFeb2022_offical <- read_excel("DFPMasterFeb2022-offical.xlsx")## New names:
## • `ID` -> `ID...1`
## • `IL-1b` -> `IL-1b...83`
## • `IL-1b` -> `IL-1b...103`
## • `ID` -> `ID...107`
## • `` -> `...111`change file name:
DFP_Complete <- DFPMasterFeb2022_offical
colnames(DFP_Complete)## [1] "ID...1" "WAFR"
## [3] "NATAM" "EURO"
## [5] "AGE" "D.O.B."
## [7] "SEX" "NEUROPATHY (Y OR N)"
## [9] "DIABETES (Y OR N)" "HYPERTENSION"
## [11] "HEIGHT" "WEIGHT"
## [13] "BMI" "A1C"
## [15] "GLUCOSE, SERUM" "MICROALBUMIN"
## [17] "CREATININE" "BUN/ CREATININE"
## [19] "C- REACTIVE PROTEIN" "CHOLESTEROL, TOTAL"
## [21] "CHOLESTEROL, HDL" "CHOLESTEROL, LDL"
## [23] "TRIGLYCERIDES" "CHOLESTEROL, VLDL"
## [25] "SODIUM" "POTASSIUM"
## [27] "CALCIUM" "IGFBP2 rs11711877"
## [29] "IGFBP2rs7633675" "IGFBP2 rs6769511"
## [31] "IGFBP2 rs6765808" "IRAK4 rs4251545"
## [33] "IRAK4 rs1470579" "a1c.cat"
## [35] "trigly.cat" "hdl.cat"
## [37] "glucose.cat" "mir17.avg.16.5p"
## [39] "mir17.avg.221.5p" "mir17.ct"
## [41] "mir142.avg.16.5p" "mir142.avg.221.3p"
## [43] "mr142.ct" "Batch"
## [45] "Fractalkine" "IFN-a2"
## [47] "IL-3" "IL-4"
## [49] "IL-7" "TNFa"
## [51] "Total PCSK9" "Active PCSK9"
## [53] "Ratio (A/T) PCSK9" "Lp(a)"
## [55] "A1AT (mg/dL) - ELISA" "A1AT (mg/dL) - R&D ELISA"
## [57] "A1AT (mg/dL) - Turbidity Assay" "Met PCSK9 Gene"
## [59] "PCSK9 R46L (rs11591147)" "PCSK9 R127S (rs28942111)"
## [61] "PCSK9 Y142* (rs67608943)" "PCSK9 C679* (rs28362286)"
## [63] "PCSK9 A443P (rs28362263)" "PCSK9 G670E (rs505151)"
## [65] "PCSK9 V474I (rs562556)" "ALT"
## [67] "AST" "Ratio AST/ALT"
## [69] "TGFa" "G-CSF"
## [71] "GM-GSF" "INF-g"
## [73] "IL-10" "MCP-3"
## [75] "IL-12p40" "IL-12p70"
## [77] "IL-13" "IL-15"
## [79] "IL-17a" "IL-1ra"
## [81] "IL-1a" "IL-9"
## [83] "IL-1b...83" "IL-2"
## [85] "IL-5" "IL-6"
## [87] "IL-8" "IP-10"
## [89] "MCP-1" "MIP-1a"
## [91] "MIP-1b" "TNFb"
## [93] "ACTH" "DKK1"
## [95] "IL-6-Bone" "Insulin"
## [97] "Leptin" "TNF-a-Bone"
## [99] "OPG" "OC"
## [101] "OPN" "SOST"
## [103] "IL-1b...103" "PTH"
## [105] "FGF23" "sIL7R"
## [107] "ID...107" "WtBS"
## [109] "WtPI" "DeltaWeight"
## [111] "...111" "GDF15_rs1058587"
## [113] "GPER_rs11544331" "PCSK9_rs11591147"
## [115] "HNFA1_rs1169288" "A1AT_rs1303"
## [117] "A1AT_rs17580" "APOH_rs1801690"
## [119] "APOH_rs1801692" "IL4R_rs1805011"
## [121] "IL4R_rs1805016" "HNF41_rs1805098"
## [123] "ABCA1_rs2230806" "HNF13_rs2464196"
## [125] "PCSK9_rs28362263" "PCSK9_rs28362286"
## [127] "A1AT_rs28929474" "PCSK9_rs28942111"
## [129] "HNF43_rs2943549" "APOH_rs35449692"
## [131] "IL3_rs40401" "IRAK4_rs4251545"
## [133] "APOH_rs4581" "PCSK9_rs505151"
## [135] "PCSK9_rs562556" "A1AT_rs6647"
## [137] "PCSK9_rs67608943" "IL7R_rs6897932"
## [139] "A1AT_rs709932" "Dkk1out"fix names with spaces:
names(DFP_Complete)[15]<-"GluSer"
names(DFP_Complete)[18]<-"BunCre"
names(DFP_Complete)[19]<-"CRP"
names(DFP_Complete)[20]<-"Total_Chol"
names(DFP_Complete)[21]<-"HDL_Chol"
names(DFP_Complete)[22]<-"LDL_Chol"
names(DFP_Complete)[24]<-"VLDL_Chol"
names(DFP_Complete)[46]<-"IFNa2"
names(DFP_Complete)[47]<-"IL3"
names(DFP_Complete)[48]<-"IL4"
names(DFP_Complete)[49]<-"IL7"
names(DFP_Complete)[51]<-"Total_PCSK9"
names(DFP_Complete)[52]<-"Active_PCSK9"
names(DFP_Complete)[53]<-"Ratio_PCSK9"
names(DFP_Complete)[54]<-"LPA"
names(DFP_Complete)[55]<-"A1AT_ELISA"
names(DFP_Complete)[56]<-"A1AT_RnD"
names(DFP_Complete)[57]<-"A1AT_Turb"
names(DFP_Complete)[68]<-"Ratio_AST_ALT"
names(DFP_Complete)[70]<-"G_CSF"
names(DFP_Complete)[71]<-"GM_CSF"
names(DFP_Complete)[72]<-"IFNg"
names(DFP_Complete)[73]<-"IL10"
names(DFP_Complete)[74]<-"MCP3"
names(DFP_Complete)[75]<-"IL12p40"
names(DFP_Complete)[76]<-"IL12p70"
names(DFP_Complete)[77]<-"IL13"
names(DFP_Complete)[78]<-"IL15"
names(DFP_Complete)[79]<-"IL17a"
names(DFP_Complete)[80]<-"IL1ra"
names(DFP_Complete)[81]<-"IL1a"
names(DFP_Complete)[82]<-"IL9"
names(DFP_Complete)[83]<-"IL1b80"
names(DFP_Complete)[84]<-"IL2"
names(DFP_Complete)[85]<-"IL5"
names(DFP_Complete)[86]<-"IL6"
names(DFP_Complete)[87]<-"IL8"
names(DFP_Complete)[88]<-"IP10"
names(DFP_Complete)[89]<-"MCP1"
names(DFP_Complete)[90]<-"MIP1a"
names(DFP_Complete)[91]<-"MIP1b"
names(DFP_Complete)[95]<-"IL6_Bone"
names(DFP_Complete)[98]<-"TNFa_Bone"
names(DFP_Complete)[103]<-"IL1b_100"Descriptive Statistics for population splitting ancestry data into quartiles:
#West African Ancestry
WAFRquart <- quantile(DFP_Complete$WAFR, probs = c(0.25, 0.5, 0.75), na.rm = TRUE)
WAFRquart## 25% 50% 75%
## 0.68665 0.76380 0.83795#European Ancestry
EUROquart <- quantile(DFP_Complete$EURO, probs = c(0.25, 0.5, 0.75), na.rm = TRUE)
EUROquart## 25% 50% 75%
## 0.09675 0.19180 0.29505#Native American Ancestry
NATAMquart <- quantile(DFP_Complete$NATAM, probs = c(0.25, 0.5, 0.75), na.rm = TRUE)
NATAMquart## 25% 50% 75%
## 0.02150 0.03785 0.06955subset data by ancestry: West African Ancestry:
#subset
WAFRlow <- subset(DFP_Complete, WAFR <= 0.68665)
WAFRmid <- subset(DFP_Complete, WAFR >= 0.68666 & WAFR <= 0.83794)
WAFRhigh <- subset(DFP_Complete, WAFR >= 0.83795)European Ancestry:
#subset
EUROlow <- subset(DFP_Complete, EURO <= 0.09675)
EUROmid <- subset(DFP_Complete, EURO >= 0.09676 & EURO <= 0.29504)
EUROhigh <- subset(DFP_Complete, EURO >= 0.29505)Native American Ancestry:
#subset
NATAMlow <- subset(DFP_Complete, NATAM <= 0.02150)
NATAMmid <- subset(DFP_Complete, NATAM >= 0.02151 & NATAM <= 0.06954)
NATAMhigh <- subset(DFP_Complete, NATAM >= 0.06955)histogram of WAFR:
hist(DFP_Complete$WAFR,
breaks = 200,
main = "Histogram of % WAFR",
col = "lightblue",
border = "black")
histogram of EURO:
hist(DFP_Complete$EURO,
breaks = 100,
main = "Histogram of % EURO",
col = "coral",
border = "black")
histogram of NATAM:
hist(DFP_Complete$NATAM,
breaks = 100,
main = "Histogram of % NATAM",
col = "darkgoldenrod1",
border = "black")
creating data set that removes rows/individuals with NA (no values for ancestry data):
WAFRlab<- subset(DFP_Complete, !is.na(DFP_Complete$WAFR))
EUROlab<- subset(DFP_Complete, !is.na(DFP_Complete$EURO))
NATAMlab<- subset(DFP_Complete, !is.na(DFP_Complete$NATAM))creating a new column within the current data set:
WAFRquart## 25% 50% 75%
## 0.68665 0.76380 0.83795WAFRlab$WAFRPercentage[WAFRlab$WAFR < 0.68665] <- 0## Warning: Unknown or uninitialised column: `WAFRPercentage`.WAFRlab$WAFRPercentage[(WAFRlab$WAFR >= 0.68666) & (WAFRlab$WAFR <= 0.83794)] <- 1
WAFRlab$WAFRPercentage[WAFRlab$WAFR > 0.83795] <- 2
WAFRlab$WAFRPercentage## [1] 2 2 1 1 1 0 1 1 0 1 1 2 1 1 0 0 1 1 0 0 2 2 1 1 1 0 2 1 0 0 1 0 1 1 0 0 1
## [38] 2 0 1 1 1 1 2 0 0 2 1 0 0 0 2 2 0 1 1 2 2 1 1 2 2 2 0 1 1 0 0 1 2 2 1 2 2
## [75] 0 0 0 0 1 1 1 1 1 0 2 0 1 1 1 1 1 1 2 2 0 2 1 1 0 1 2 1 1 2 1 2 1 1 1 1 1
## [112] 0 2 1 1 0 1 1 1 1 2 1 1 0 1 0 1 0 1 1 0 1 0 0 2 1 1 1 1 1 1 1 0 0 2 1 1 0
## [149] 2 2 2 2 1 1 2 2 2 2 1 2 0 0 1 2 0 1 1 1 1 1 1 2 2 1 1 0 1 0 0 2 1 1 1 1 2
## [186] 0 2 2 1 1 2 1 1 0 0 0 2 1 1 2 0 2 1 1 1 1 2EUROquart## 25% 50% 75%
## 0.09675 0.19180 0.29505EUROlab$EUROPercentage[EUROlab$EURO < 0.09675] <- 0## Warning: Unknown or uninitialised column: `EUROPercentage`.EUROlab$EUROPercentage[(EUROlab$EURO >= 0.09676) & (EUROlab$EURO <= 0.29504)] <- 1
EUROlab$EUROPercentage[EUROlab$EURO > 0.29505] <- 2
EUROlab$EUROPercentage## [1] 0 0 1 1 1 2 1 1 1 1 1 0 1 0 2 2 1 0 2 2 0 0 2 1 1 2 1 1 2 2 1 1 1 0 2 2 1
## [38] 0 2 1 1 1 1 0 2 2 0 1 2 2 1 0 0 2 1 1 0 0 1 1 0 0 0 2 1 0 2 2 1 1 0 1 1 0
## [75] 2 2 2 1 1 1 1 1 1 2 1 1 1 1 1 1 1 1 0 1 2 0 0 0 1 1 0 1 0 1 1 0 1 1 1 1 1
## [112] 2 0 1 1 2 1 0 1 1 0 1 1 2 1 1 1 2 1 1 2 1 2 2 0 1 1 1 1 1 1 0 2 1 0 1 1 2
## [149] 0 0 1 0 1 0 0 0 1 1 1 0 2 2 1 0 2 1 1 1 1 1 1 0 0 1 1 2 1 2 1 1 1 1 1 1 0
## [186] 2 0 1 1 1 0 1 1 2 2 2 0 1 0 1 2 0 0 0 1 1 0 1 1 2 2 0 1 0 1 0 2 2 1 2 1 0
## [223] 1 2 0 2 2 2 2 0 2 2 2 2 2NATAMquart## 25% 50% 75%
## 0.02150 0.03785 0.06955NATAMlab$NATAMPercentage[NATAMlab$NATAM < 0.02150] <- 0## Warning: Unknown or uninitialised column: `NATAMPercentage`.NATAMlab$NATAMPercentage[(NATAMlab$NATAM >= 0.02151) & (NATAMlab$NATAM <= 0.06954)] <- 1
NATAMlab$NATAMPercentage[NATAMlab$NATAM > 0.06955] <- 2
NATAMlab$NATAMPercentage## [1] 1 2 1 2 2 1 1 1 1 1 1 1 1 2 1 2 2 2 1 1 1 1 0 0 2
## [26] 1 0 2 0 1 0 2 1 2 1 1 0 1 0 1 1 1 1 1 1 1 1 1 1 1
## [51] 2 2 0 1 1 1 1 2 1 2 2 2 1 0 1 2 1 0 0 0 1 1 1 2 0
## [76] 1 1 2 0 0 1 1 0 0 1 2 1 1 0 1 1 1 1 1 0 2 2 2 2 1
## [101] 2 0 2 1 1 1 1 0 0 1 1 2 2 0 1 1 1 2 1 0 0 1 2 2 2
## [126] 2 0 0 1 1 0 0 0 0 1 0 0 0 1 1 1 2 1 2 1 1 2 0 1 2
## [151] 1 2 0 2 2 2 0 1 0 2 0 2 2 1 1 0 1 1 1 1 0 1 1 1 1
## [176] 1 2 1 1 0 0 1 2 0 2 1 0 1 0 2 1 0 NA 1 1 0 1 NA 2 1
## [201] 0 1 2 2 0 1 0creating a new column that is a replicate of the old column (labeling our original conditions with text):
WAFRlab$WAFRPerLab <- WAFRlab$WAFRPercentage
WAFRlab$WAFRPerLab[WAFRlab$WAFRPerLab == 0] <- "Low"
WAFRlab$WAFRPerLab[WAFRlab$WAFRPerLab == 1] <- "Mid"
WAFRlab$WAFRPerLab[WAFRlab$WAFRPerLab == 2] <- "High"
EUROlab$EUROPerLab <- EUROlab$EUROPercentage
EUROlab$EUROPerLab[EUROlab$EUROPerLab == 0] <- "Low"
EUROlab$EUROPerLab[EUROlab$EUROPerLab == 1] <- "Mid"
EUROlab$EUROPerLab[EUROlab$EUROPerLab == 2] <- "High"
NATAMlab$NATAMPerLab <- NATAMlab$NATAMPercentage
NATAMlab$NATAMPerLab[NATAMlab$NATAMPerLab == 0] <- "Low"
NATAMlab$NATAMPerLab[NATAMlab$NATAMPerLab == 1] <- "Mid"
NATAMlab$NATAMPerLab[NATAMlab$NATAMPerLab == 2] <- "High"Immune regulators:
Fractalkine:
Fractalkine WAFR ancestry plot with mean bar:***
Fractalkine.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=Fractalkine)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("Fractalkine \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Fractalkine Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
Fractalkine.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Fractalkine.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Fractalkine.compare)## Warning: Removed 42 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 42 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 42 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 42 rows containing missing values or values outside the scale range
## (`geom_point()`).
Fractalkine WAFR ancestry plot with box plot (Color):***
Fractalkine.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=Fractalkine, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("Fractalkine \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Fractalkine Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
Fractalkine.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Fractalkine.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Fractalkine.compare)## Warning: Removed 42 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 42 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 42 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 42 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 42 rows containing missing values or values outside the scale range
## (`geom_point()`).
Fractalkine EURO ancestry plot with mean bar:
Fractalkine.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=Fractalkine)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Fractalkine \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Fractalkine Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
Fractalkine.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Fractalkine.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Fractalkine.compare)## Warning: Removed 58 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 58 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 58 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 58 rows containing missing values or values outside the scale range
## (`geom_point()`).
Fractalkine EURO ancestry plot with box plot (Color):
Fractalkine.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=Fractalkine, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Fractalkine \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Fractalkine Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
Fractalkine.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Fractalkine.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Fractalkine.compare)## Warning: Removed 58 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 58 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 58 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 58 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 58 rows containing missing values or values outside the scale range
## (`geom_point()`).
Fractalkine NATAM ancestry plot with mean bar:***
Fractalkine.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=Fractalkine)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Fractalkine \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Fractalkine Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
Fractalkine.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Fractalkine.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Fractalkine.compare)## Warning: Removed 44 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 44 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 44 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 44 rows containing missing values or values outside the scale range
## (`geom_point()`).
Fractalkine NATAM ancestry plot with box plot (Color):***
Fractalkine.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=Fractalkine, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Fractalkine \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Fractalkine Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
Fractalkine.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Fractalkine.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Fractalkine.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 42 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 44 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 44 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 44 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 44 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNa2:
IFNa2 WAFR ancestry plot with mean bar:
IFNa2.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IFNa2)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IFNa2 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNa2 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IFNa2.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNa2.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNa2.compare)## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNa2 WAFR ancestry plot with box plot (Color):
IFNa2.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IFNa2, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IFNa2 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNa2 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IFNa2.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNa2.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNa2.compare)## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNa2 EURO ancestry plot with mean bar:
IFNa2.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IFNa2)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IFNa2 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNa2 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IFNa2.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNa2.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNa2.compare)## Warning: Removed 67 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 67 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 67 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 67 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNa2 EURO ancestry plot with box plot (Color):
IFNa2.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IFNa2, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IFNa2 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNa2 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IFNa2.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNa2.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNa2.compare)## Warning: Removed 67 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 67 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 67 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 67 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 67 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNa2 NATAM ancestry plot with mean bar:
IFNa2.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IFNa2)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IFNa2 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNa2 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IFNa2.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNa2.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNa2.compare)## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNa2 NATAM ancestry plot with box plot (Color):
IFNa2.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IFNa2, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IFNa2 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNa2 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IFNa2.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNa2.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNa2.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 48 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL3:
IL3 WAFR ancestry plot with mean bar:
IL3.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL3)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL3 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL3 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL3.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL3.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL3.compare)## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 80 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL3 WAFR ancestry plot with box plot (Color):
IL3.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL3, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL3 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL3 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL3.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL3.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL3.compare)## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 80 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL3 EURO ancestry plot with mean bar:
IL3.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL3)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL3 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL3 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL3.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL3.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL3.compare)## Warning: Removed 98 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 98 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 98 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 98 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL3 EURO ancestry plot with box plot (Color):
IL3.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL3, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL3 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL3 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL3.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL3.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL3.compare)## Warning: Removed 98 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 98 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 98 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 98 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 98 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL3 NATAM ancestry plot with mean bar:***
IL3.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL3)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL3 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL3 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL3.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL3.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL3.compare)## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 80 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL3 NATAM ancestry plot with box plot (Color):***
IL3.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL3, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL3 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL3 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL3.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL3.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL3.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 78 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 80 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 80 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL4:
IL4 WAFR ancestry plot with mean bar:
IL4.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL4)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL4 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL4 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL4.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL4.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL4.compare)## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 72 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL4 WAFR ancestry plot with box plot (Color):
IL4.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL4, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL4 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL4 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL4.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL4.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL4.compare)## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 72 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL4 EURO ancestry plot with mean bar:
IL4.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL4)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL4 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL4 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL4.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL4.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL4.compare)## Warning: Removed 90 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 90 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 90 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 90 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL4 EURO ancestry plot with box plot (Color):***
IL4.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL4, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL4 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL4 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL4.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL4.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL4.compare)## Warning: Removed 90 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 90 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 90 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 90 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 90 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL4 NATAM ancestry plot with mean bar:***
IL4.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL4)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL4 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL4 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL4.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL4.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL4.compare)## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 72 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL4 NATAM ancestry plot with box plot (Color):
IL4.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL4, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL4 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL4 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL4.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL4.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL4.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 70 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 72 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 72 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL7:
IL7 WAFR ancestry plot with mean bar:
IL7.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL7)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL7 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL7 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL7.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL7.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL7.compare)## Warning: Removed 60 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 60 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 60 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 60 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL7 WAFR ancestry plot with box plot (Color):
IL7.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL7, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL7 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL7 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL7.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL7.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL7.compare)## Warning: Removed 60 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 60 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 60 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 60 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 60 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL7 EURO ancestry plot with mean bar:
IL7.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL7)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL7 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL7 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL7.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL7.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL7.compare)## Warning: Removed 79 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 79 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 79 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 79 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL7 EURO ancestry plot with box plot (Color):
IL7.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL7, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL7 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL7 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL7.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL7.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL7.compare)## Warning: Removed 79 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 79 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 79 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 79 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 79 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL7 NATAM ancestry plot with mean bar:
IL7.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL7)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL7 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL7 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL7.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL7.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL7.compare)## Warning: Removed 61 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 61 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 61 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 61 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL7 NATAM ancestry plot with box plot (Color):
IL7.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL7, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL7 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL7 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL7.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL7.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL7.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 59 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 61 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 61 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 61 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 61 rows containing missing values or values outside the scale range
## (`geom_point()`).
sIL7R:
sIL7R WAFR ancestry plot with mean bar:
sIL7R.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=sIL7R)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("sIL7R \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("sIL7R Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
sIL7R.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
sIL7R.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = sIL7R.compare)## Warning: Removed 143 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 143 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 143 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 143 rows containing missing values or values outside the scale range
## (`geom_point()`).
sIL7R WAFR ancestry plot with box plot (Color):
sIL7R.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=sIL7R, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("sIL7R \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("sIL7R Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
sIL7R.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
sIL7R.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = sIL7R.compare)## Warning: Removed 143 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 143 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 143 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 143 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 143 rows containing missing values or values outside the scale range
## (`geom_point()`).
sIL7R EURO ancestry plot with mean bar:
sIL7R.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=sIL7R)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("sIL7R \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("sIL7R Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
sIL7R.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
sIL7R.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = sIL7R.compare)## Warning: Removed 164 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 164 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 164 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 164 rows containing missing values or values outside the scale range
## (`geom_point()`).
sIL7R EURO ancestry plot with box plot (Color):
sIL7R.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=sIL7R, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("sIL7R \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("sIL7R Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
sIL7R.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
sIL7R.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = sIL7R.compare)## Warning: Removed 164 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 164 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 164 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 164 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 164 rows containing missing values or values outside the scale range
## (`geom_point()`).
sIL7R NATAM ancestry plot with mean bar:
sIL7R.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=sIL7R)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("sIL7R \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("sIL7R Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
sIL7R.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
sIL7R.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = sIL7R.compare)## Warning: Removed 144 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 144 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 144 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 144 rows containing missing values or values outside the scale range
## (`geom_point()`).
sIL7R NATAM ancestry plot with box plot (Color):
sIL7R.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=sIL7R, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("sIL7R \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("sIL7R Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
sIL7R.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
sIL7R.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = sIL7R.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 142 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 144 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 144 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 144 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 144 rows containing missing values or values outside the scale range
## (`geom_point()`).
TNFa:
TNFa WAFR ancestry plot with mean bar:***
TNFa.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=TNFa)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("TNFa \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TNFa Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
TNFa.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TNFa.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TNFa.compare)## Warning: Removed 37 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 37 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 37 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 37 rows containing missing values or values outside the scale range
## (`geom_point()`).
TNFa WAFR ancestry plot with box plot (Color):***
TNFa.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=TNFa, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("TNFa \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TNFa Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
TNFa.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TNFa.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TNFa.compare)## Warning: Removed 37 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 37 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 37 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 37 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 37 rows containing missing values or values outside the scale range
## (`geom_point()`).
TNFa EURO ancestry plot with mean bar:
TNFa.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=TNFa)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("TNFa \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TNFa Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
TNFa.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TNFa.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TNFa.compare)## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_point()`).
TNFa EURO ancestry plot with box plot (Color):
TNFa.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=TNFa, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("TNFa \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TNFa Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
TNFa.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TNFa.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TNFa.compare)## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_point()`).
TNFa NATAM ancestry plot with mean bar:
TNFa.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=TNFa)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("TNFa \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TNFa Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
TNFa.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TNFa.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TNFa.compare)## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 39 rows containing missing values or values outside the scale range
## (`geom_point()`).
TNFa NATAM ancestry plot with box plot (Color):
TNFa.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=TNFa, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("TNFa \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TNFa Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
TNFa.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TNFa.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TNFa.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 37 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 39 rows containing missing values or values outside the scale range
## (`geom_point()`).
G_CSF:
G_CSF WAFR ancestry plot with mean bar:
G_CSF.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=G_CSF)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("G_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("G_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
G_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
G_CSF.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = G_CSF.compare)## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 156 rows containing missing values or values outside the scale range
## (`geom_point()`).
G_CSF WAFR ancestry plot with box plot (Color):
G_CSF.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=G_CSF, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("G_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("G_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
G_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
G_CSF.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = G_CSF.compare)## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 156 rows containing missing values or values outside the scale range
## (`geom_point()`).
G_CSF EURO ancestry plot with mean bar:
G_CSF.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=G_CSF)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("G_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("G_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
G_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
G_CSF.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = G_CSF.compare)## Warning: Removed 176 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 176 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 176 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 176 rows containing missing values or values outside the scale range
## (`geom_point()`).
G_CSF EURO ancestry plot with box plot (Color):
G_CSF.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=G_CSF, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("G_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("G_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
G_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
G_CSF.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = G_CSF.compare)## Warning: Removed 176 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 176 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 176 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 176 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 176 rows containing missing values or values outside the scale range
## (`geom_point()`).
G_CSF NATAM ancestry plot with mean bar:
G_CSF.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=G_CSF)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("G_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("G_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
G_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
G_CSF.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = G_CSF.compare)## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 157 rows containing missing values or values outside the scale range
## (`geom_point()`).
G_CSF NATAM ancestry plot with box plot (Color):
G_CSF.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=G_CSF, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("G_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("G_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
G_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
G_CSF.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = G_CSF.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 157 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 157 rows containing missing values or values outside the scale range
## (`geom_point()`).
GM_CSF:
GM_CSF WAFR ancestry plot with mean bar:
GM_CSF.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=GM_CSF)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("GM_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GM_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
GM_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GM_CSF.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GM_CSF.compare)## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 162 rows containing missing values or values outside the scale range
## (`geom_point()`).
GM_CSF WAFR ancestry plot with box plot (Color):
GM_CSF.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=GM_CSF, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("GM_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GM_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
GM_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GM_CSF.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GM_CSF.compare)## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 162 rows containing missing values or values outside the scale range
## (`geom_point()`).
GM_CSF EURO ancestry plot with mean bar:
GM_CSF.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=GM_CSF)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("GM_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GM_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
GM_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GM_CSF.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GM_CSF.compare)## Warning: Removed 184 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 184 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 184 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 184 rows containing missing values or values outside the scale range
## (`geom_point()`).
GM_CSF EURO ancestry plot with box plot (Color):
GM_CSF.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=GM_CSF, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("GM_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GM_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
GM_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GM_CSF.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GM_CSF.compare)## Warning: Removed 184 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 184 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 184 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 184 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 184 rows containing missing values or values outside the scale range
## (`geom_point()`).
GM_CSF NATAM ancestry plot with mean bar:
GM_CSF.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=GM_CSF)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("GM_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GM_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
GM_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GM_CSF.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GM_CSF.compare)## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 163 rows containing missing values or values outside the scale range
## (`geom_point()`).
GM_CSF NATAM ancestry plot with box plot (Color):
GM_CSF.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=GM_CSF, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("GM_CSF \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GM_CSF Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
GM_CSF.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GM_CSF.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GM_CSF.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 161 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 163 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNg:
IFNg WAFR ancestry plot with mean bar:
IFNg.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IFNg)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IFNg \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNg Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IFNg.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNg.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNg.compare)## Warning: Removed 161 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 161 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 161 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 161 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNg WAFR ancestry plot with box plot (Color):
IFNg.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IFNg, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IFNg \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNg Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IFNg.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNg.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNg.compare)## Warning: Removed 161 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 161 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 161 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 161 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 161 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNg EURO ancestry plot with mean bar:
IFNg.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IFNg)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IFNg \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNg Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IFNg.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNg.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNg.compare)## Warning: Removed 182 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 182 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 182 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 182 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNg EURO ancestry plot with box plot (Color):
IFNg.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IFNg, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IFNg \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNg Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IFNg.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNg.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNg.compare)## Warning: Removed 182 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 182 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 182 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 182 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 182 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNg NATAM ancestry plot with mean bar:
IFNg.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IFNg)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IFNg \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNg Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IFNg.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNg.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNg.compare)## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 162 rows containing missing values or values outside the scale range
## (`geom_point()`).
IFNg NATAM ancestry plot with box plot (Color):
IFNg.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IFNg, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IFNg \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IFNg Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IFNg.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IFNg.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IFNg.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 160 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 162 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL17a:
IL17a WAFR ancestry plot with mean bar:
IL17a.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL17a)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL17a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL17a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL17a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL17a.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL17a.compare)## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 168 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL17a WAFR ancestry plot with box plot (Color):
IL17a.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL17a, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL17a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL17a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL17a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL17a.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL17a.compare)## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 168 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL17a EURO ancestry plot with mean bar:
IL17a.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL17a)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL17a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL17a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL17a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL17a.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL17a.compare)## Warning: Removed 191 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 191 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 191 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 191 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL17a EURO ancestry plot with box plot (Color):
IL17a.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL17a, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL17a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL17a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL17a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL17a.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL17a.compare)## Warning: Removed 191 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 191 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 191 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 191 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 191 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL17a NATAM ancestry plot with mean bar:
IL17a.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL17a)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL17a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL17a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL17a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL17a.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL17a.compare)## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 168 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL17a NATAM ancestry plot with box plot (Color):
IL17a.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL17a, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL17a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL17a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL17a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL17a.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL17a.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 166 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 168 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 168 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL1ra:
IL1ra WAFR ancestry plot with mean bar:
IL1ra.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL1ra)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL1ra \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL1ra Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL1ra.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL1ra.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL1ra.compare)## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 162 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL1ra WAFR ancestry plot with box plot (Color):
IL1ra.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IL1ra, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IL1ra \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL1ra Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL1ra.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL1ra.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL1ra.compare)## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 162 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 162 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL1ra EURO ancestry plot with mean bar:***
IL1ra.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL1ra)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL1ra \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL1ra Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL1ra.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL1ra.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL1ra.compare)## Warning: Removed 183 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 183 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 183 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 183 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL1ra EURO ancestry plot with box plot (Color):***
IL1ra.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IL1ra, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IL1ra \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL1ra Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL1ra.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL1ra.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL1ra.compare)## Warning: Removed 183 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 183 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 183 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 183 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 183 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL1ra NATAM ancestry plot with mean bar:
IL1ra.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL1ra)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL1ra \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL1ra Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IL1ra.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL1ra.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL1ra.compare)## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 163 rows containing missing values or values outside the scale range
## (`geom_point()`).
IL1ra NATAM ancestry plot with box plot (Color):
IL1ra.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IL1ra, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IL1ra \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IL1ra Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IL1ra.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IL1ra.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IL1ra.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 161 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 163 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 163 rows containing missing values or values outside the scale range
## (`geom_point()`).
IP10:
IP10 WAFR ancestry plot with mean bar:***
IP10.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IP10)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IP10 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IP10 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IP10.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IP10.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IP10.compare)## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 155 rows containing missing values or values outside the scale range
## (`geom_point()`).
IP10 WAFR ancestry plot with box plot (Color):***
IP10.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=IP10, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("IP10 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IP10 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IP10.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IP10.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IP10.compare)## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 155 rows containing missing values or values outside the scale range
## (`geom_point()`).
IP10 EURO ancestry plot with mean bar:***
IP10.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IP10)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IP10 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IP10 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IP10.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IP10.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IP10.compare)## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 175 rows containing missing values or values outside the scale range
## (`geom_point()`).
IP10 EURO ancestry plot with box plot (Color):***
IP10.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=IP10, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("IP10 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IP10 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IP10.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IP10.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IP10.compare)## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 175 rows containing missing values or values outside the scale range
## (`geom_point()`).
IP10 NATAM ancestry plot with mean bar:
IP10.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IP10)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IP10 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IP10 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
IP10.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IP10.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IP10.compare)## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 156 rows containing missing values or values outside the scale range
## (`geom_point()`).
IP10 NATAM ancestry plot with box plot (Color):
IP10.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=IP10, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("IP10 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("IP10 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
IP10.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
IP10.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = IP10.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 154 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 156 rows containing missing values or values outside the scale range
## (`geom_point()`).
MCP1:
MCP1 WAFR ancestry plot with mean bar:
MCP1.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=MCP1)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("MCP1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MCP1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MCP1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MCP1.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MCP1.compare)## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 155 rows containing missing values or values outside the scale range
## (`geom_point()`).
MCP1 WAFR ancestry plot with box plot (Color):
MCP1.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=MCP1, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("MCP1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MCP1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MCP1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MCP1.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MCP1.compare)## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 155 rows containing missing values or values outside the scale range
## (`geom_point()`).
MCP1 EURO ancestry plot with mean bar:
MCP1.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=MCP1)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("MCP1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MCP1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MCP1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MCP1.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MCP1.compare)## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 175 rows containing missing values or values outside the scale range
## (`geom_point()`).
MCP1 EURO ancestry plot with box plot (Color):
MCP1.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=MCP1, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("MCP1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MCP1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MCP1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MCP1.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MCP1.compare)## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 175 rows containing missing values or values outside the scale range
## (`geom_point()`).
MCP1 NATAM ancestry plot with mean bar:***
MCP1.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=MCP1)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("MCP1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MCP1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MCP1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MCP1.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MCP1.compare)## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 156 rows containing missing values or values outside the scale range
## (`geom_point()`).
MCP1 NATAM ancestry plot with box plot (Color):***
MCP1.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=MCP1, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("MCP1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MCP1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MCP1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MCP1.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MCP1.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 154 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 156 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1a:
MIP1a WAFR ancestry plot with mean bar:
MIP1a.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=MIP1a)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("MIP1a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MIP1a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1a.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1a.compare)## Warning: Removed 171 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 171 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 171 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 171 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1a WAFR ancestry plot with box plot (Color):
MIP1a.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=MIP1a, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("MIP1a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MIP1a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1a.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1a.compare)## Warning: Removed 171 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 171 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 171 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 171 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 171 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1a EURO ancestry plot with mean bar:
MIP1a.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=MIP1a)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("MIP1a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MIP1a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1a.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1a.compare)## Warning: Removed 193 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 193 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 193 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 193 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1a EURO ancestry plot with box plot (Color):
MIP1a.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=MIP1a, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("MIP1a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MIP1a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1a.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1a.compare)## Warning: Removed 193 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 193 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 193 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 193 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 193 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1a NATAM ancestry plot with mean bar:***
MIP1a.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=MIP1a)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("MIP1a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MIP1a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1a.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1a.compare)## Warning: Removed 172 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 172 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 172 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 172 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1a NATAM ancestry plot with box plot (Color):***
MIP1a.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=MIP1a, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("MIP1a \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1a Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MIP1a.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1a.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1a.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 170 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 172 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 172 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 172 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 172 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1b:
MIP1b WAFR ancestry plot with mean bar:
MIP1b.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=MIP1b)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("MIP1b \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1b Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MIP1b.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1b.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1b.compare)## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 155 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1b WAFR ancestry plot with box plot (Color):
MIP1b.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=MIP1b, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("MIP1b \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1b Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MIP1b.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1b.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1b.compare)## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 155 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 155 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1b EURO ancestry plot with mean bar:
MIP1b.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=MIP1b)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("MIP1b \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1b Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MIP1b.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1b.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1b.compare)## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 175 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1b EURO ancestry plot with box plot (Color):
MIP1b.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=MIP1b, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("MIP1b \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1b Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MIP1b.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1b.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1b.compare)## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 175 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 175 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1b NATAM ancestry plot with mean bar:
MIP1b.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=MIP1b)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("MIP1b \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1b Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MIP1b.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1b.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1b.compare)## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 156 rows containing missing values or values outside the scale range
## (`geom_point()`).
MIP1b NATAM ancestry plot with box plot (Color):
MIP1b.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=MIP1b, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("MIP1b \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MIP1b Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MIP1b.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MIP1b.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MIP1b.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 154 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 156 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 156 rows containing missing values or values outside the scale range
## (`geom_point()`).
DKK1:
DKK1 WAFR ancestry plot with mean bar:***
DKK1.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=DKK1)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("DKK1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("DKK1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
DKK1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
DKK1.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = DKK1.compare)## Warning: Removed 95 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 95 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 95 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 95 rows containing missing values or values outside the scale range
## (`geom_point()`).
DKK1 WAFR ancestry plot with box plot (Color):***
DKK1.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=DKK1, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("DKK1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("DKK1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
DKK1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
DKK1.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = DKK1.compare)## Warning: Removed 95 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 95 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 95 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 95 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 95 rows containing missing values or values outside the scale range
## (`geom_point()`).
DKK1 EURO ancestry plot with mean bar:***
DKK1.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=DKK1)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("DKK1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("DKK1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
DKK1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
DKK1.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = DKK1.compare)## Warning: Removed 109 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 109 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 109 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 109 rows containing missing values or values outside the scale range
## (`geom_point()`).
DKK1 EURO ancestry plot with box plot (Color):***
DKK1.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=DKK1, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("DKK1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("DKK1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
DKK1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
DKK1.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = DKK1.compare)## Warning: Removed 109 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 109 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 109 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 109 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 109 rows containing missing values or values outside the scale range
## (`geom_point()`).
DKK1 NATAM ancestry plot with mean bar:
DKK1.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=DKK1)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("DKK1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("DKK1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
DKK1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
DKK1.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = DKK1.compare)## Warning: Removed 96 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 96 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 96 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 96 rows containing missing values or values outside the scale range
## (`geom_point()`).
DKK1 NATAM ancestry plot with box plot (Color):
DKK1.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=DKK1, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("DKK1 \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("DKK1 Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
DKK1.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
DKK1.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = DKK1.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 94 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 96 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 96 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 96 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 96 rows containing missing values or values outside the scale range
## (`geom_point()`).
Liver Damage Markers:
ALT:
ALT WAFR ancestry plot with mean bar:
ALT.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=ALT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
ALT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = ALT.compare)## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 38 rows containing missing values or values outside the scale range
## (`geom_point()`).
ALT WAFR ancestry plot with box plot (Color):
ALT.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=ALT, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
ALT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = ALT.compare)## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 38 rows containing missing values or values outside the scale range
## (`geom_point()`).
ALT EURO ancestry plot with mean bar:
ALT.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=ALT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
ALT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = ALT.compare)## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_point()`).
ALT EURO ancestry plot with box plot (Color):
ALT.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=ALT, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
ALT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = ALT.compare)## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 50 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 50 rows containing missing values or values outside the scale range
## (`geom_point()`).
ALT NATAM ancestry plot with mean bar:***
ALT.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=ALT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("ALT \n (U/L)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
ALT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = ALT.compare)## Warning: Removed 40 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 40 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 40 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 40 rows containing missing values or values outside the scale range
## (`geom_point()`).
ALT NATAM ancestry plot with box plot (Color):***
ALT.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=ALT, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("ALT \n ALT \n (U/L)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
ALT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = ALT.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 40 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 40 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 40 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 40 rows containing missing values or values outside the scale range
## (`geom_point()`).
AST:
AST WAFR ancestry plot with mean bar:
AST.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=AST)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("AST \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("AST Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
AST.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
AST.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = AST.compare)## Warning: Removed 36 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 36 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 36 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 36 rows containing missing values or values outside the scale range
## (`geom_point()`).
AST WAFR ancestry plot with box plot (Color):
AST.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=AST, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("AST \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("AST Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
AST.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
AST.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = AST.compare)## Warning: Removed 36 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 36 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 36 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 36 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 36 rows containing missing values or values outside the scale range
## (`geom_point()`).
AST EURO ancestry plot with mean bar:
AST.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=AST)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("AST \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("AST Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
AST.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
AST.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = AST.compare)## Warning: Removed 48 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 48 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 48 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 48 rows containing missing values or values outside the scale range
## (`geom_point()`).
AST EURO ancestry plot with box plot (Color):
AST.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=AST, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("AST \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("AST Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
AST.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
AST.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = AST.compare)## Warning: Removed 48 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 48 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 48 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 48 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 48 rows containing missing values or values outside the scale range
## (`geom_point()`).
AST NATAM ancestry plot with mean bar:
AST.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=AST)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("AST \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("AST Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
AST.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
AST.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = AST.compare)## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 38 rows containing missing values or values outside the scale range
## (`geom_point()`).
AST NATAM ancestry plot with box plot (Color):
AST.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=AST, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("AST \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("AST Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
AST.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
AST.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = AST.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 36 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 38 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 38 rows containing missing values or values outside the scale range
## (`geom_point()`).
Ratio_AST_ALT:
Ratio_AST_ALT WAFR ancestry plot with mean bar:
Ratio_AST_ALT.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=Ratio_AST_ALT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("Ratio_AST_ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Ratio_AST_ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
Ratio_AST_ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Ratio_AST_ALT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Ratio_AST_ALT.compare)## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 39 rows containing missing values or values outside the scale range
## (`geom_point()`).
Ratio_AST_ALT WAFR ancestry plot with box plot (Color):
Ratio_AST_ALT.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=Ratio_AST_ALT, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("Ratio_AST_ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Ratio_AST_ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
Ratio_AST_ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Ratio_AST_ALT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Ratio_AST_ALT.compare)## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 39 rows containing missing values or values outside the scale range
## (`geom_point()`).
Ratio_AST_ALT EURO ancestry plot with mean bar:
Ratio_AST_ALT.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=Ratio_AST_ALT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Ratio_AST_ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Ratio_AST_ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
Ratio_AST_ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Ratio_AST_ALT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Ratio_AST_ALT.compare)## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 51 rows containing missing values or values outside the scale range
## (`geom_point()`).
Ratio_AST_ALT EURO ancestry plot with box plot (Color):
Ratio_AST_ALT.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=Ratio_AST_ALT, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Ratio_AST_ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Ratio_AST_ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
Ratio_AST_ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Ratio_AST_ALT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Ratio_AST_ALT.compare)## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 51 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 51 rows containing missing values or values outside the scale range
## (`geom_point()`).
Ratio_AST_ALT NATAM ancestry plot with mean bar:
Ratio_AST_ALT.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=Ratio_AST_ALT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Ratio_AST_ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Ratio_AST_ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
Ratio_AST_ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Ratio_AST_ALT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Ratio_AST_ALT.compare)## Warning: Removed 41 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 41 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 41 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 41 rows containing missing values or values outside the scale range
## (`geom_point()`).
Ratio_AST_ALT NATAM ancestry plot with box plot (Color):
Ratio_AST_ALT.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=Ratio_AST_ALT, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Ratio_AST_ALT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Ratio_AST_ALT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
Ratio_AST_ALT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Ratio_AST_ALT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Ratio_AST_ALT.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 39 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 41 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 41 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 41 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 41 rows containing missing values or values outside the scale range
## (`geom_point()`).
MICROALBUMIN:
MICROALBUMIN WAFR ancestry plot with mean bar:
MICROALBUMIN.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=MICROALBUMIN)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("MICROALBUMIN \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MICROALBUMIN Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MICROALBUMIN.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MICROALBUMIN.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MICROALBUMIN.compare)## Warning: Removed 21 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 21 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 21 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 21 rows containing missing values or values outside the scale range
## (`geom_point()`).
MICROALBUMIN WAFR ancestry plot with box plot (Color):
MICROALBUMIN.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=MICROALBUMIN, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("MICROALBUMIN \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MICROALBUMIN Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MICROALBUMIN.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MICROALBUMIN.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MICROALBUMIN.compare)## Warning: Removed 21 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 21 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 21 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 21 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 21 rows containing missing values or values outside the scale range
## (`geom_point()`).
MICROALBUMIN EURO ancestry plot with mean bar:
MICROALBUMIN.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=MICROALBUMIN)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("MICROALBUMIN \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MICROALBUMIN Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MICROALBUMIN.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MICROALBUMIN.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MICROALBUMIN.compare)## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 23 rows containing missing values or values outside the scale range
## (`geom_point()`).
MICROALBUMIN EURO ancestry plot with box plot (Color):
MICROALBUMIN.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=MICROALBUMIN, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("MICROALBUMIN \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MICROALBUMIN Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MICROALBUMIN.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MICROALBUMIN.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MICROALBUMIN.compare)## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 23 rows containing missing values or values outside the scale range
## (`geom_point()`).
MICROALBUMIN NATAM ancestry plot with mean bar:
MICROALBUMIN.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=MICROALBUMIN)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("MICROALBUMIN \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MICROALBUMIN Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
MICROALBUMIN.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MICROALBUMIN.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MICROALBUMIN.compare)## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 23 rows containing missing values or values outside the scale range
## (`geom_point()`).
MICROALBUMIN NATAM ancestry plot with box plot (Color):
MICROALBUMIN.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=MICROALBUMIN, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("MICROALBUMIN \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("MICROALBUMIN Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
MICROALBUMIN.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
MICROALBUMIN.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = MICROALBUMIN.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 21 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 23 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 23 rows containing missing values or values outside the scale range
## (`geom_point()`).
CREATININE:
CREATININE WAFR ancestry plot with mean bar:
CREATININE.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=CREATININE)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("CREATININE \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CREATININE Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
CREATININE.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CREATININE.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CREATININE.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
CREATININE WAFR ancestry plot with box plot (Color):
CREATININE.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=CREATININE, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("CREATININE \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CREATININE Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
CREATININE.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CREATININE.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CREATININE.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
CREATININE EURO ancestry plot with mean bar:
CREATININE.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=CREATININE)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("CREATININE \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CREATININE Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
CREATININE.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CREATININE.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CREATININE.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
CREATININE EURO ancestry plot with box plot (Color):
CREATININE.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=CREATININE, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("CREATININE \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CREATININE Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
CREATININE.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CREATININE.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CREATININE.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
CREATININE NATAM ancestry plot with mean bar:
CREATININE.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=CREATININE)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("CREATININE \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CREATININE Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
CREATININE.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CREATININE.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CREATININE.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
CREATININE NATAM ancestry plot with box plot (Color):
CREATININE.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=CREATININE, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("CREATININE \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CREATININE Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
CREATININE.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CREATININE.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CREATININE.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
BunCre:
BunCre WAFR ancestry plot with mean bar:
BunCre.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=BunCre)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("BunCre \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BunCre Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
BunCre.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BunCre.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BunCre.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
BunCre WAFR ancestry plot with box plot (Color):
BunCre.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=BunCre, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("BunCre \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BunCre Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
BunCre.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BunCre.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BunCre.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
BunCre EURO ancestry plot with mean bar:
BunCre.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=BunCre)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("BunCre \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BunCre Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
BunCre.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BunCre.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BunCre.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
BunCre EURO ancestry plot with box plot (Color):
BunCre.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=BunCre, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("BunCre \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BunCre Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
BunCre.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BunCre.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BunCre.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
BunCre NATAM ancestry plot with mean bar:***
BunCre.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=BunCre)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Bun/creatinine ratio \n (mg/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Bun/creatinine ratio by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
BunCre.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BunCre.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BunCre.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
BunCre NATAM ancestry plot with box plot (Color):***
BunCre.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=BunCre, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Bun/creatinine ratio \n (mg/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Bun/creatinine ratio by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
BunCre.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BunCre.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BunCre.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
CRP:
CRP WAFR ancestry plot with mean bar:
CRP.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=CRP)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("CRP \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CRP Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
CRP.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CRP.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CRP.compare)## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 100 rows containing missing values or values outside the scale range
## (`geom_point()`).
CRP WAFR ancestry plot with box plot (Color):
CRP.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=CRP, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("CRP \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CRP Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
CRP.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CRP.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CRP.compare)## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 100 rows containing missing values or values outside the scale range
## (`geom_point()`).
CRP EURO ancestry plot with mean bar:
CRP.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=CRP)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("CRP \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CRP Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
CRP.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CRP.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CRP.compare)## Warning: Removed 116 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 116 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 116 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 116 rows containing missing values or values outside the scale range
## (`geom_point()`).
CRP EURO ancestry plot with box plot (Color):
CRP.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=CRP, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("CRP \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CRP Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
CRP.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CRP.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CRP.compare)## Warning: Removed 116 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 116 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 116 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 116 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 116 rows containing missing values or values outside the scale range
## (`geom_point()`).
CRP NATAM ancestry plot with mean bar:
CRP.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=CRP)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("CRP \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CRP Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
CRP.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CRP.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CRP.compare)## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 100 rows containing missing values or values outside the scale range
## (`geom_point()`).
CRP NATAM ancestry plot with box plot (Color):
CRP.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=CRP, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("CRP \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CRP Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
CRP.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CRP.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CRP.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 98 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 100 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 100 rows containing missing values or values outside the scale range
## (`geom_point()`).
Lipid Biomarkers:
Total_Chol:
Total_Chol WAFR ancestry plot with mean bar:
Total_Chol.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=Total_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("Total_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Total_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
Total_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Total_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Total_Chol.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
Total_Chol WAFR ancestry plot with box plot (Color):
Total_Chol.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=Total_Chol, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("Total_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Total_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
Total_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Total_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Total_Chol.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
Total_Chol EURO ancestry plot with mean bar:
Total_Chol.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=Total_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Total_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Total_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
Total_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Total_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Total_Chol.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
Total_Chol EURO ancestry plot with box plot (Color):
Total_Chol.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=Total_Chol, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Total_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Total_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
Total_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Total_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Total_Chol.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
Total_Chol NATAM ancestry plot with mean bar:
Total_Chol.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=Total_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Total_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Total_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
Total_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Total_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Total_Chol.compare)## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
Total_Chol NATAM ancestry plot with box plot (Color):
Total_Chol.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=Total_Chol, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Total_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Total_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
Total_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
Total_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = Total_Chol.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
HDL_Chol:
HDL_Chol WAFR ancestry plot with mean bar:***
HDL_Chol.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=HDL_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("HDL Cholesterol \n (mg/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("HDL Cholesterol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
HDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HDL_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HDL_Chol.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
HDL_Chol WAFR ancestry plot with box plot (Color):***
HDL_Chol.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=HDL_Chol, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("HDL Cholesterol \n (mg/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("HDL Cholesterol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
HDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HDL_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HDL_Chol.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
HDL_Chol EURO ancestry plot with mean bar:
HDL_Chol.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=HDL_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("HDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("HDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
HDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HDL_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HDL_Chol.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
HDL_Chol EURO ancestry plot with box plot (Color):
HDL_Chol.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=HDL_Chol, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("HDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("HDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
HDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HDL_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HDL_Chol.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
HDL_Chol NATAM ancestry plot with mean bar:
HDL_Chol.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=HDL_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("HDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("HDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
HDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HDL_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HDL_Chol.compare)## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
HDL_Chol NATAM ancestry plot with box plot (Color):
HDL_Chol.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=HDL_Chol, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("HDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("HDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
HDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HDL_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HDL_Chol.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
LDL_Chol:
LDL_Chol WAFR ancestry plot with mean bar:
LDL_Chol.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=LDL_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("LDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("LDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
LDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LDL_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LDL_Chol.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
LDL_Chol WAFR ancestry plot with box plot (Color):
LDL_Chol.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=LDL_Chol, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("LDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("LDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
LDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LDL_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LDL_Chol.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
LDL_Chol EURO ancestry plot with mean bar:
LDL_Chol.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=LDL_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("LDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("LDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
LDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LDL_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LDL_Chol.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
LDL_Chol EURO ancestry plot with box plot (Color):
LDL_Chol.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=LDL_Chol, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("LDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("LDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
LDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LDL_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LDL_Chol.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
LDL_Chol NATAM ancestry plot with mean bar:***
LDL_Chol.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=LDL_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("LDL Cholesterol \n (mg/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("LDL Cholesterol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
LDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LDL_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LDL_Chol.compare)## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 8 rows containing missing values or values outside the scale range
## (`geom_point()`).
LDL_Chol NATAM ancestry plot with box plot (Color):***
LDL_Chol.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=LDL_Chol, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("LDL Cholesterol \n (pm/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("LDL Cholesterol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
LDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LDL_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LDL_Chol.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 8 rows containing missing values or values outside the scale range
## (`geom_point()`).
TRIGLYCERIDES:
TRIGLYCERIDES WAFR ancestry plot with mean bar:
TRIGLYCERIDES.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=TRIGLYCERIDES)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("TRIGLYCERIDES \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TRIGLYCERIDES Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
TRIGLYCERIDES.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TRIGLYCERIDES.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TRIGLYCERIDES.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
TRIGLYCERIDES WAFR ancestry plot with box plot (Color):
TRIGLYCERIDES.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=TRIGLYCERIDES, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("TRIGLYCERIDES \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TRIGLYCERIDES Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
TRIGLYCERIDES.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TRIGLYCERIDES.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TRIGLYCERIDES.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
TRIGLYCERIDES EURO ancestry plot with mean bar:
TRIGLYCERIDES.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=TRIGLYCERIDES)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("TRIGLYCERIDES \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TRIGLYCERIDES Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
TRIGLYCERIDES.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TRIGLYCERIDES.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TRIGLYCERIDES.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
TRIGLYCERIDES EURO ancestry plot with box plot (Color):
TRIGLYCERIDES.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=TRIGLYCERIDES, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("TRIGLYCERIDES \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TRIGLYCERIDES Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
TRIGLYCERIDES.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TRIGLYCERIDES.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TRIGLYCERIDES.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
TRIGLYCERIDES NATAM ancestry plot with mean bar:
TRIGLYCERIDES.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=TRIGLYCERIDES)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("TRIGLYCERIDES \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TRIGLYCERIDES Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
TRIGLYCERIDES.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TRIGLYCERIDES.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TRIGLYCERIDES.compare)## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
TRIGLYCERIDES NATAM ancestry plot with box plot (Color):
TRIGLYCERIDES.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=TRIGLYCERIDES, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("TRIGLYCERIDES \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("TRIGLYCERIDES Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
TRIGLYCERIDES.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
TRIGLYCERIDES.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = TRIGLYCERIDES.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
VLDL_Chol:
VLDL_Chol WAFR ancestry plot with mean bar:
VLDL_Chol.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=VLDL_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("VLDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("VLDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
VLDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
VLDL_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = VLDL_Chol.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
VLDL_Chol WAFR ancestry plot with box plot (Color):
VLDL_Chol.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=VLDL_Chol, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("VLDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("VLDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
VLDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
VLDL_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = VLDL_Chol.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
VLDL_Chol EURO ancestry plot with mean bar:
VLDL_Chol.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=VLDL_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("VLDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("VLDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
VLDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
VLDL_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = VLDL_Chol.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
VLDL_Chol EURO ancestry plot with box plot (Color):
VLDL_Chol.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=VLDL_Chol, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("VLDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("VLDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
VLDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
VLDL_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = VLDL_Chol.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
VLDL_Chol NATAM ancestry plot with mean bar:
VLDL_Chol.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=VLDL_Chol)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("VLDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("VLDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
VLDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
VLDL_Chol.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = VLDL_Chol.compare)## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 8 rows containing missing values or values outside the scale range
## (`geom_point()`).
VLDL_Chol NATAM ancestry plot with box plot (Color):
VLDL_Chol.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=VLDL_Chol, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("VLDL_Chol \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("VLDL_Chol Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
VLDL_Chol.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
VLDL_Chol.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = VLDL_Chol.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 8 rows containing missing values or values outside the scale range
## (`geom_point()`).
LPA:
LPA WAFR ancestry plot with mean bar:***
LPA.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=LPA)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("Lp(a) \n (mg/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Lp(a) Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
LPA.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LPA.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LPA.compare)## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 114 rows containing missing values or values outside the scale range
## (`geom_point()`).
LPA WAFR ancestry plot with box plot (Color):***
LPA.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=LPA, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("Lp(a) \n (mg/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Lp(a) Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
LPA.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LPA.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LPA.compare)## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 114 rows containing missing values or values outside the scale range
## (`geom_point()`).
LPA EURO ancestry plot with mean bar:***
LPA.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=LPA)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Lp(a) \n (mg/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Lp(a) Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
LPA.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LPA.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LPA.compare)## Warning: Removed 137 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 137 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 137 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 137 rows containing missing values or values outside the scale range
## (`geom_point()`).
LPA EURO ancestry plot with box plot (Color):***
LPA.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=LPA, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Lp(a) \n (mg/dL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Lp(a) Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
LPA.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LPA.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LPA.compare)## Warning: Removed 137 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 137 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 137 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 137 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 137 rows containing missing values or values outside the scale range
## (`geom_point()`).
LPA NATAM ancestry plot with mean bar:
LPA.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=LPA)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("LPA \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("LPA Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
LPA.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LPA.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LPA.compare)## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 114 rows containing missing values or values outside the scale range
## (`geom_point()`).
LPA NATAM ancestry plot with box plot (Color):
LPA.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=LPA, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("LPA \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("LPA Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
LPA.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
LPA.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = LPA.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 112 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 114 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 114 rows containing missing values or values outside the scale range
## (`geom_point()`).
Clinical Parameters:
HEIGHT:
HEIGHT WAFR ancestry plot with mean bar:
HEIGHT.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=HEIGHT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("HEIGHT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("HEIGHT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
HEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HEIGHT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HEIGHT.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
HEIGHT WAFR ancestry plot with box plot (Color):
HEIGHT.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=HEIGHT, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("HEIGHT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("HEIGHT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
HEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HEIGHT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HEIGHT.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
HEIGHT EURO ancestry plot with mean bar:***
HEIGHT.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=HEIGHT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Height \n (in)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Height Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
HEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HEIGHT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HEIGHT.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
HEIGHT EURO ancestry plot with box plot (Color):***
HEIGHT.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=HEIGHT, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("Height \n (in)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Height Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
HEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HEIGHT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HEIGHT.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
HEIGHT NATAM ancestry plot with mean bar:***
HEIGHT.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=HEIGHT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Height \n (in)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Height by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
HEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HEIGHT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HEIGHT.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
HEIGHT NATAM ancestry plot with box plot (Color):***
HEIGHT.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=HEIGHT, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Height \n (in)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Height by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
HEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
HEIGHT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = HEIGHT.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
WEIGHT:
WEIGHT WAFR ancestry plot with mean bar:
WEIGHT.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=WEIGHT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("WEIGHT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("WEIGHT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
WEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
WEIGHT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = WEIGHT.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
WEIGHT WAFR ancestry plot with box plot (Color):
WEIGHT.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=WEIGHT, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("WEIGHT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("WEIGHT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
WEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
WEIGHT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = WEIGHT.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
WEIGHT EURO ancestry plot with mean bar:
WEIGHT.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=WEIGHT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("WEIGHT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("WEIGHT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
WEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
WEIGHT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = WEIGHT.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
WEIGHT EURO ancestry plot with box plot (Color):
WEIGHT.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=WEIGHT, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("WEIGHT \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("WEIGHT Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
WEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
WEIGHT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = WEIGHT.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
WEIGHT NATAM ancestry plot with mean bar:***
WEIGHT.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=WEIGHT)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Weight \n (lbs)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Weight by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
WEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
WEIGHT.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = WEIGHT.compare)## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
WEIGHT NATAM ancestry plot with box plot (Color):***
WEIGHT.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=WEIGHT, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Weight \n (lbs)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Weight by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
WEIGHT.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
WEIGHT.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = WEIGHT.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
BMI:
BMI WAFR ancestry plot with mean bar:
BMI.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=BMI)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("BMI \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BMI Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
BMI.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BMI.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BMI.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
BMI WAFR ancestry plot with box plot (Color):
BMI.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=BMI, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("BMI \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BMI Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
BMI.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BMI.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BMI.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
BMI EURO ancestry plot with mean bar:
BMI.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=BMI)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("BMI \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BMI Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
BMI.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BMI.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BMI.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
BMI EURO ancestry plot with box plot (Color):
BMI.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=BMI, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("BMI \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BMI Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
BMI.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BMI.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BMI.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
BMI NATAM ancestry plot with mean bar:***
BMI.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=BMI)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("BMI \n (kg/m2)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BMI by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
BMI.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BMI.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BMI.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
BMI NATAM ancestry plot with box plot (Color):***
BMI.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=BMI, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("BMI \n (kg/m2)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("BMI by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
BMI.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
BMI.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = BMI.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
A1C:
A1C WAFR ancestry plot with mean bar:
A1C.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=A1C)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("A1C \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("A1C Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
A1C.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
A1C.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = A1C.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
A1C WAFR ancestry plot with box plot (Color):
A1C.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=A1C, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("A1C \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("A1C Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
A1C.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
A1C.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = A1C.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
A1C EURO ancestry plot with mean bar:
A1C.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=A1C)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("A1C \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("A1C Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
A1C.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
A1C.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = A1C.compare)## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 7 rows containing missing values or values outside the scale range
## (`geom_point()`).
A1C EURO ancestry plot with box plot (Color):
A1C.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=A1C, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("A1C \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("A1C Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
A1C.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
A1C.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = A1C.compare)## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 7 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 7 rows containing missing values or values outside the scale range
## (`geom_point()`).
A1C NATAM ancestry plot with mean bar:
A1C.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=A1C)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("A1C \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("A1C Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
A1C.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
A1C.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = A1C.compare)## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 8 rows containing missing values or values outside the scale range
## (`geom_point()`).
A1C NATAM ancestry plot with box plot (Color):
A1C.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=A1C, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("A1C \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("A1C Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
A1C.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
A1C.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = A1C.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 8 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 8 rows containing missing values or values outside the scale range
## (`geom_point()`).
GluSer:
GluSer WAFR ancestry plot with mean bar:
GluSer.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=GluSer)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("GluSer \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GluSer Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
GluSer.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GluSer.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GluSer.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
GluSer WAFR ancestry plot with box plot (Color):
GluSer.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=GluSer, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("GluSer \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GluSer Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
GluSer.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GluSer.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GluSer.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
GluSer EURO ancestry plot with mean bar:
GluSer.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=GluSer)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("GluSer \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GluSer Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
GluSer.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GluSer.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GluSer.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
GluSer EURO ancestry plot with box plot (Color):
GluSer.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=GluSer, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("GluSer \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GluSer Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
GluSer.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GluSer.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GluSer.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
GluSer NATAM ancestry plot with mean bar:
GluSer.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=GluSer)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("GluSer \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GluSer Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
GluSer.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GluSer.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GluSer.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
GluSer NATAM ancestry plot with box plot (Color):
GluSer.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=GluSer, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("GluSer \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("GluSer Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
GluSer.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
GluSer.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = GluSer.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
Kidney/Electrolyte Markers:
SODIUM:
SODIUM WAFR ancestry plot with mean bar:
SODIUM.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=SODIUM)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("SODIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("SODIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
SODIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
SODIUM.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = SODIUM.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
SODIUM WAFR ancestry plot with box plot (Color):
SODIUM.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=SODIUM, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("SODIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("SODIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
SODIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
SODIUM.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = SODIUM.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
SODIUM EURO ancestry plot with mean bar:
SODIUM.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=SODIUM)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("SODIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("SODIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
SODIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
SODIUM.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = SODIUM.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
SODIUM EURO ancestry plot with box plot (Color):
SODIUM.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=SODIUM, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("SODIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("SODIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
SODIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
SODIUM.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = SODIUM.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
SODIUM NATAM ancestry plot with mean bar:
SODIUM.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=SODIUM)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("SODIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("SODIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
SODIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
SODIUM.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = SODIUM.compare)## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
SODIUM NATAM ancestry plot with box plot (Color):
SODIUM.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=SODIUM, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("SODIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("SODIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
SODIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
SODIUM.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = SODIUM.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
POTASSIUM:
POTASSIUM WAFR ancestry plot with mean bar:
POTASSIUM.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=POTASSIUM)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("POTASSIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("POTASSIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
POTASSIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
POTASSIUM.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = POTASSIUM.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
POTASSIUM WAFR ancestry plot with box plot (Color):
POTASSIUM.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=POTASSIUM, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("POTASSIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("POTASSIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
POTASSIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
POTASSIUM.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = POTASSIUM.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
POTASSIUM EURO ancestry plot with mean bar:
POTASSIUM.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=POTASSIUM)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("POTASSIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("POTASSIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
POTASSIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
POTASSIUM.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = POTASSIUM.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
POTASSIUM EURO ancestry plot with box plot (Color):
POTASSIUM.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=POTASSIUM, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("POTASSIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("POTASSIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
POTASSIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
POTASSIUM.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = POTASSIUM.compare)## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 4 rows containing missing values or values outside the scale range
## (`geom_point()`).
POTASSIUM NATAM ancestry plot with mean bar:***
POTASSIUM.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=POTASSIUM)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Potassium \n (mmol/L)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Potassium Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
POTASSIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
POTASSIUM.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = POTASSIUM.compare)## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
POTASSIUM NATAM ancestry plot with box plot (Color):***
POTASSIUM.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=POTASSIUM, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("Potassium \n (mmol/L") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("Potassium Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
POTASSIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
POTASSIUM.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = POTASSIUM.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 4 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 6 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 6 rows containing missing values or values outside the scale range
## (`geom_point()`).
CALCIUM:
CALCIUM WAFR ancestry plot with mean bar:
CALCIUM.plot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=CALCIUM)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("CALCIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CALCIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
CALCIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CALCIUM.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CALCIUM.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
CALCIUM WAFR ancestry plot with box plot (Color):
CALCIUM.cplot <- ggplot(data=WAFRlab, aes(x=WAFRPerLab, y=CALCIUM, colour = WAFRPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of WAFR") +
ylab("CALCIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CALCIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
CALCIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CALCIUM.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CALCIUM.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
CALCIUM EURO ancestry plot with mean bar:
CALCIUM.plot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=CALCIUM)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("CALCIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CALCIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
CALCIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CALCIUM.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CALCIUM.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
CALCIUM EURO ancestry plot with box plot (Color):
CALCIUM.cplot <- ggplot(data=EUROlab, aes(x=EUROPerLab, y=CALCIUM, colour = EUROPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of EURO") +
ylab("CALCIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CALCIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
CALCIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CALCIUM.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CALCIUM.compare)## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 3 rows containing missing values or values outside the scale range
## (`geom_point()`).
CALCIUM NATAM ancestry plot with mean bar:
CALCIUM.plot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=CALCIUM)) +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("CALCIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CALCIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5))
#create mean comparison groups
CALCIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CALCIUM.plot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CALCIUM.compare)## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).
CALCIUM NATAM ancestry plot with box plot (Color):
CALCIUM.cplot <- ggplot(data=NATAMlab, aes(x=NATAMPerLab, y=CALCIUM, colour = NATAMPerLab)) +
geom_boxplot() +
theme_classic() +
geom_jitter(position=position_jitter(0.1)) +
stat_summary(fun = median, fun.min = median, fun.max = median, geom = "crossbar", width = 0.5) +
xlab("% of NATAM") +
ylab("CALCIUM \n (pg/mL)") +
scale_x_discrete(limit = c("Low","Mid","High")) +
ggtitle("CALCIUM Levels by \n Ancestry") +
theme(plot.title = element_text(hjust = 0.5), legend.position = "none")
#create mean comparison groups
CALCIUM.compare <- list( c("Low", "Mid"), c("Mid", "High"), c("Low", "High"))
#add p-value to plot while comparing means
CALCIUM.cplot + stat_compare_means(method = "t.test", label.y = 3500) +
# Visualize: Specify the comparisons you want
stat_compare_means(method = 't.test', comparisons = CALCIUM.compare)## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`stat_boxplot()`).## Warning: Removed 3 rows containing non-finite outside the scale range
## (`stat_boxplot()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Unknown or uninitialised column: `p`.## Warning: Computation failed in `stat_compare_means()`.
## Caused by error:
## ! argument "x" is missing, with no default## Warning: Removed 5 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_point()`).