R Notebook
This notebook describes the preliminary analysis of root anatomical features - along the main root developmental axis - collected by Emilly Miller - working in Magda Julkowska’s lab at Boyce Thompson Institute, Ithaca, NY.
The analysis itself was performed by Magda Julkowska
Load data
data <- read.csv("20250318_MRCrossSectionData.csv")
data$Root.Area <- as.numeric(as.character(data$Root.Area))
data$Epidermis.Cell.Individual..1 <- as.numeric(as.character(data$Epidermis.Cell.Individual..1))
data$Epidermis.Cell.Individual..2 <- as.numeric(as.character(data$Epidermis.Cell.Individual..2))
data$Epidermis.Cell.Individual..3 <- as.numeric(as.character(data$Epidermis.Cell.Individual..3))
data$Epidermis.Cell.Individual..4 <- as.numeric(as.character(data$Epidermis.Cell.Individual..4))
data$Epidermis.Total <- as.numeric(as.character(data$Epidermis.Total))
data$Cortex.Cell.individual..1 <- as.numeric(as.character(data$Cortex.Cell.individual..1))
data$Cortex.Cell.individual..2 <- as.numeric(as.character(data$Cortex.Cell.individual..2))
data$Cortex.Cell.individual..3 <- as.numeric(as.character(data$Cortex.Cell.individual..3))
data$Cortex.Cell.individual..4 <- as.numeric(as.character(data$Cortex.Cell.individual..4))
data$Cortex.Total <- as.numeric(as.character(data$Cortex.Total))
data$Endodermis.Cell.Individual..1 <- as.numeric(as.character(data$Endodermis.Cell.Individual..1))
data$Endodermis.Cell.Individual..2 <- as.numeric(as.character(data$Endodermis.Cell.Individual..2))
data$Endodermis.Cell.Individual..3 <- as.numeric(as.character(data$Endodermis.Cell.Individual..3))
data$Endodermis.Cell.Individual..4 <- as.numeric(as.character(data$Endodermis.Cell.Individual..4))
data$Endodermis.Total <- as.numeric(as.character(data$Endodermis.Total))
data$Vasculature.Cell.Size.Individual..1 <- as.numeric(as.character(data$Vasculature.Cell.Size.Individual..1))
data$Vasculature.Cell.Size.Individual..2 <- as.numeric(as.character(data$Vasculature.Cell.Size.Individual..2))
data$Vasculature.Cell.Size.Individual..3 <- as.numeric(as.character(data$Vasculature.Cell.Size.Individual..3))
data$Vasculature.Cell.Size.Individual..4 <- as.numeric(as.character(data$Vasculature.Cell.Size.Individual..4))
data$Vasculature.Total <- as.numeric(as.character(data$Vasculature.Total))
data$Number.of.Cortex.Layers <- gsub("?", "", data$Number.of.Cortex.Layers)
data$Number.of.Cortex.Layers <- as.numeric(as.character(data$Number.of.Cortex.Layers))## Warning: NAs introduced by coerciondataBulk data visualization:
OK - first let’s have a look at the overall root surface:
library(ggplot2)
library(ggpubr)
library(ggbeeswarm)
library(ggsci)## Warning: package 'ggsci' was built under R version 4.3.3my_comparisons <- list(c("MR_Proximal", "MR_Mid"), c("MR_Mid", "MR_Tip"), c("MR_Proximal", "MR_Tip"))
RootArea <- ggerrorplot(data, x = "Folder.Path", y = "Root.Area", color = "Folder.Path", fill = "Folder.Path",
desc_stat = "mean_sd", add = "jitter", ncol = 2,
xlab="", ylab= "Root Area (a.u.)", add.params = list(color = "darkgray")) + color_palette("aaas")
RootArea <- RootArea + stat_compare_means(method = "aov", label.y = 3000000)
RootArea <- RootArea + stat_compare_means(comparisons = my_comparisons)
RootArea <- RootArea + rremove("legend") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
RootArea## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
OK - let’s check other bulk traits:
EpiArea <- ggerrorplot(data, x = "Folder.Path", y = "Epidermis.Total", color = "Folder.Path", fill = "Folder.Path",
desc_stat = "mean_sd", add = "jitter", ncol = 2,
xlab="", ylab= "Epidermis Area (a.u.)", add.params = list(color = "darkgray")) + color_palette("aaas")
EpiArea <- EpiArea + stat_compare_means(method = "aov", label.y = 1000000)
EpiArea <- EpiArea + stat_compare_means(comparisons = my_comparisons)
EpiArea <- EpiArea + rremove("legend") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
EpiArea## Warning: Removed 1 row containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 1 row containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Removed 1 row containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_point()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
CorArea <- ggerrorplot(data, x = "Folder.Path", y = "Cortex.Total", color = "Folder.Path", fill = "Folder.Path",
desc_stat = "mean_sd", add = "jitter", ncol = 2,
xlab="", ylab= "Cortex Area (a.u.)", add.params = list(color = "darkgray")) + color_palette("aaas")
CorArea <- CorArea + stat_compare_means(method = "aov", label.y = 950000)
CorArea <- CorArea + stat_compare_means(comparisons = my_comparisons)
CorArea <- CorArea + rremove("legend") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
CorArea## 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: 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()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
EndoArea <- ggerrorplot(data, x = "Folder.Path", y = "Endodermis.Total", color = "Folder.Path", fill = "Folder.Path",
desc_stat = "mean_sd", add = "jitter", ncol = 2,
xlab="", ylab= "Cortex Area (a.u.)", add.params = list(color = "darkgray")) + color_palette("aaas")
EndoArea <- EndoArea + stat_compare_means(method = "aov", label.y = 400000)
EndoArea <- EndoArea + stat_compare_means(comparisons = my_comparisons)
EndoArea <- EndoArea + rremove("legend") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
EndoArea## 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: 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()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
VascArea <- ggerrorplot(data, x = "Folder.Path", y = "Vasculature.Total", color = "Folder.Path", fill = "Folder.Path",
desc_stat = "mean_sd", add = "jitter", ncol = 2,
xlab="", ylab= "Vasculature Area (a.u.)", add.params = list(color = "darkgray")) + color_palette("aaas")
VascArea <- VascArea + stat_compare_means(method = "aov", label.y = 600000)
VascArea <- VascArea + stat_compare_means(comparisons = my_comparisons)
VascArea <- VascArea + rremove("legend") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
VascArea## 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: 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()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
Individual cell size visualization
OK - now let’s have a look at the individual cell sizes within each layer.
First - we need to melt the data frame:
library(reshape2)
datadata_melt <- melt(data, id=c("Image.Name", "Folder.Path"))
data_meltnow - we need to remove all of the ..1 to ..4:
data_melt$variable <- gsub("..1", "", data_melt$variable)
data_melt$variable <- gsub("..2", "", data_melt$variable)
data_melt$variable <- gsub("..3", "", data_melt$variable)
data_melt$variable <- gsub("..4", "", data_melt$variable)
data_meltNow - let’s plot all of the variables just for the fun of it:
# we dont need all of the variables - especially count based ones:
unique(data_melt$variable)## [1] "Root.Area" "Epidermis.Cell.Individual"
## [3] "Epidermis.Total" "Cortex.Cell.individual"
## [5] "Cortex.Total" "Number.of.Cortex.Layers"
## [7] "Endodermis.Cell.Individual" "Endodermis.Total"
## [9] "Vasculature.Cell.Size.Individual" "Vasculature.Total"
## [11] "Xylem.Bundle.Sheath.Present.or.0." "Number.of.XBS"
## [13] "Surface.Area.of.XBS" "Surface.Area.of.XBS.1"
## [15] "Surface.Area.of.XB" "Surface.Area.of.XBS.5"
## [17] "Surface.Area.of.XBS.6"bye <- c("Number.of.Cortex.Layers", "Xylem.Bundle.Sheath.Present.or.0.", "Number.of.XBS",
"Surface.Area.of.XBS.5", "Surface.Area.of.XBS.6", "Surface.Area.of.XBS.7","Vasculature.Cell.Size.Individual")
data_melt2 <- subset(data_melt, !(data_melt$variable %in% bye))
data_melt2$variable <- gsub("Surface.Area.of.XBS.1", "Surface.Area.of.XB", data_melt2$variable)
data_melt2$variable <- gsub("Surface.Area.of.XBS", "Surface.Area.of.XB", data_melt2$variable)
data_melt2$value <- as.numeric(as.character(data_melt2$value))
data_melt2$Folder.Path <- factor(data_melt2$Folder.Path, levels = c("MR_Tip", "MR_Mid", "MR_Proximal"))
unique(data_melt2$variable)## [1] "Root.Area" "Epidermis.Cell.Individual"
## [3] "Epidermis.Total" "Cortex.Cell.individual"
## [5] "Cortex.Total" "Endodermis.Cell.Individual"
## [7] "Endodermis.Total" "Vasculature.Total"
## [9] "Surface.Area.of.XB"data_melt2$variable <- factor(data_melt2$variable, levels = c("Root.Area", "Epidermis.Total", "Cortex.Total", "Endodermis.Total", "Vasculature.Total", "Epidermis.Cell.Individual", "Cortex.Cell.individual", "Endodermis.Cell.Individual", "Surface.Area.of.XB"))
AllArea <- ggerrorplot(data_melt2, x = "variable", y = "value", color = "variable", fill = "variable",
desc_stat = "mean_sd", add = "jitter", ncol = 1, facet.by = "Folder.Path",
xlab="", ylab= "Area (a.u.)", add.params = list(color = "darkgray")) + color_palette("aaas")
AllArea <- AllArea + stat_compare_means(method = "aov", label.y = 3000000)
#AllArea <- AllArea + stat_compare_means(comparisons = my_comparisons)
AllArea <- AllArea + rremove("legend") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
AllArea## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Removed 106 rows containing missing values or values outside the scale range
## (`geom_point()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_segment()`).
Now - let’s add the sig. different groups to this graph:
library(stringr)
library(multcompView)
LR_Tip <- subset(data_melt2, data_melt2$Folder.Path == "MR_Tip")
LR_Mid <- subset(data_melt2, data_melt2$Folder.Path == "MR_Mid")
LR_Proximal <- subset(data_melt2, data_melt2$Folder.Path == "MR_Proximal")
LR_Tip$variable <- as.factor(LR_Tip$variable)
LR_Mid$variable <- as.factor(LR_Mid$variable)
LR_Proximal$variable <- as.factor(LR_Proximal$variable)
LR_TipOutput <- TukeyHSD(aov(value ~ variable, data = LR_Tip))
Output$variable## diff lwr
## Epidermis.Total-Root.Area -1042269.8095 -1302599.04
## Cortex.Total-Root.Area -694123.1429 -1017021.82
## Endodermis.Total-Root.Area -1393876.1429 -1716774.82
## Vasculature.Total-Root.Area -1312651.1429 -1635549.82
## Epidermis.Cell.Individual-Root.Area -1457827.1929 -1663318.65
## Cortex.Cell.individual-Root.Area -1453661.5357 -1651395.78
## Endodermis.Cell.Individual-Root.Area -1460477.3929 -1665968.85
## Surface.Area.of.XB-Root.Area -1460003.5873 -1695815.44
## Cortex.Total-Epidermis.Total 348146.6667 17273.98
## Endodermis.Total-Epidermis.Total -351606.3333 -682479.02
## Vasculature.Total-Epidermis.Total -270381.3333 -601254.02
## Epidermis.Cell.Individual-Epidermis.Total -415557.3833 -633364.45
## Cortex.Cell.individual-Epidermis.Total -411391.7262 -621895.91
## Endodermis.Cell.Individual-Epidermis.Total -418207.5833 -636014.65
## Surface.Area.of.XB-Epidermis.Total -417733.7778 -664351.71
## Endodermis.Total-Cortex.Total -699753.0000 -1081811.86
## Vasculature.Total-Cortex.Total -618528.0000 -1000586.86
## Epidermis.Cell.Individual-Cortex.Total -763704.0500 -1053414.53
## Cortex.Cell.individual-Cortex.Total -759538.3929 -1043799.28
## Endodermis.Cell.Individual-Cortex.Total -766354.2500 -1056064.73
## Surface.Area.of.XB-Cortex.Total -765880.4444 -1077830.20
## Vasculature.Total-Endodermis.Total 81225.0000 -300833.86
## Epidermis.Cell.Individual-Endodermis.Total -63951.0500 -353661.53
## Cortex.Cell.individual-Endodermis.Total -59785.3929 -344046.28
## Endodermis.Cell.Individual-Endodermis.Total -66601.2500 -356311.73
## Surface.Area.of.XB-Endodermis.Total -66127.4444 -378077.20
## Epidermis.Cell.Individual-Vasculature.Total -145176.0500 -434886.53
## Cortex.Cell.individual-Vasculature.Total -141010.3929 -425271.28
## Endodermis.Cell.Individual-Vasculature.Total -147826.2500 -437536.73
## Surface.Area.of.XB-Vasculature.Total -147352.4444 -459302.20
## Cortex.Cell.individual-Epidermis.Cell.Individual 4165.6571 -132828.65
## Endodermis.Cell.Individual-Epidermis.Cell.Individual -2650.2000 -150620.96
## Surface.Area.of.XB-Epidermis.Cell.Individual -2176.3944 -189995.02
## Endodermis.Cell.Individual-Cortex.Cell.individual -6815.8571 -143810.16
## Surface.Area.of.XB-Cortex.Cell.individual -6342.0516 -185640.49
## Surface.Area.of.XB-Endodermis.Cell.Individual 473.8056 -187344.82
## upr p adj
## Epidermis.Total-Root.Area -781940.58 4.353726e-10
## Cortex.Total-Root.Area -371224.47 3.458049e-08
## Endodermis.Total-Root.Area -1070977.47 4.353689e-10
## Vasculature.Total-Root.Area -989752.47 4.353713e-10
## Epidermis.Cell.Individual-Root.Area -1252335.73 4.353682e-10
## Cortex.Cell.individual-Root.Area -1255927.29 4.353682e-10
## Endodermis.Cell.Individual-Root.Area -1254985.93 4.353682e-10
## Surface.Area.of.XB-Root.Area -1224191.74 4.353682e-10
## Cortex.Total-Epidermis.Total 679019.35 3.140723e-02
## Endodermis.Total-Epidermis.Total -20733.65 2.852460e-02
## Vasculature.Total-Epidermis.Total 60491.35 2.024132e-01
## Epidermis.Cell.Individual-Epidermis.Total -197750.32 1.079176e-06
## Cortex.Cell.individual-Epidermis.Total -200887.54 5.628991e-07
## Endodermis.Cell.Individual-Epidermis.Total -200400.52 9.103739e-07
## Surface.Area.of.XB-Epidermis.Total -171115.84 1.989739e-05
## Endodermis.Total-Cortex.Total -317694.14 3.107753e-06
## Vasculature.Total-Cortex.Total -236469.14 5.297565e-05
## Epidermis.Cell.Individual-Cortex.Total -473993.57 4.595735e-10
## Cortex.Cell.individual-Cortex.Total -475277.50 4.494447e-10
## Endodermis.Cell.Individual-Cortex.Total -476643.77 4.564487e-10
## Surface.Area.of.XB-Cortex.Total -453930.69 8.055954e-10
## Vasculature.Total-Endodermis.Total 463283.86 9.989746e-01
## Epidermis.Cell.Individual-Endodermis.Total 225759.43 9.986562e-01
## Cortex.Cell.individual-Endodermis.Total 224475.50 9.990514e-01
## Endodermis.Cell.Individual-Endodermis.Total 223109.23 9.982049e-01
## Surface.Area.of.XB-Endodermis.Total 245822.31 9.989959e-01
## Epidermis.Cell.Individual-Vasculature.Total 144534.43 8.062206e-01
## Cortex.Cell.individual-Vasculature.Total 143250.50 8.147248e-01
## Endodermis.Cell.Individual-Vasculature.Total 141884.23 7.903412e-01
## Surface.Area.of.XB-Vasculature.Total 164597.31 8.520421e-01
## Cortex.Cell.individual-Epidermis.Cell.Individual 141159.96 1.000000e+00
## Endodermis.Cell.Individual-Epidermis.Cell.Individual 145320.56 1.000000e+00
## Surface.Area.of.XB-Epidermis.Cell.Individual 185642.23 1.000000e+00
## Endodermis.Cell.Individual-Cortex.Cell.individual 130178.45 1.000000e+00
## Surface.Area.of.XB-Cortex.Cell.individual 172956.38 1.000000e+00
## Surface.Area.of.XB-Endodermis.Cell.Individual 188292.43 1.000000e+00P7 = Output$variable[,'p adj']
stat.test<- multcompLetters(P7)
testc <- as.data.frame(stat.test$Letters)
testc$group2 <- rownames(testc)
testc$group1 <- rownames(testc)
testc$variable <- rownames(testc)
testc$variable <- rownames(testc)
colnames(testc)[1] <- "Tukey"
testc$Folder.Path <- "MR_Tip"
testcOutput <- TukeyHSD(aov(value ~ variable, data = LR_Mid))
Output$variable## diff lwr
## Epidermis.Total-Root.Area -1.138096e+06 -1516477.0
## Cortex.Total-Root.Area -1.040540e+06 -1434370.7
## Endodermis.Total-Root.Area -1.446697e+06 -1840528.6
## Vasculature.Total-Root.Area -1.268012e+06 -1661843.4
## Epidermis.Cell.Individual-Root.Area -1.632194e+06 -1931329.7
## Cortex.Cell.individual-Root.Area -1.632205e+06 -1931341.7
## Endodermis.Cell.Individual-Root.Area -1.634223e+06 -1945094.1
## Cortex.Total-Epidermis.Total 9.755671e+04 -296274.4
## Endodermis.Total-Epidermis.Total -3.086011e+05 -702432.3
## Vasculature.Total-Epidermis.Total -1.299160e+05 -523747.1
## Epidermis.Cell.Individual-Epidermis.Total -4.940972e+05 -793233.5
## Cortex.Cell.individual-Epidermis.Total -4.941092e+05 -793245.4
## Endodermis.Cell.Individual-Epidermis.Total -4.961263e+05 -806997.8
## Endodermis.Total-Cortex.Total -4.061578e+05 -814855.7
## Vasculature.Total-Cortex.Total -2.274727e+05 -636170.6
## Epidermis.Cell.Individual-Cortex.Total -5.916539e+05 -910108.8
## Cortex.Cell.individual-Cortex.Total -5.916659e+05 -910120.7
## Endodermis.Cell.Individual-Cortex.Total -5.936830e+05 -923185.8
## Vasculature.Total-Endodermis.Total 1.786852e+05 -230012.7
## Epidermis.Cell.Individual-Endodermis.Total -1.854961e+05 -503950.9
## Cortex.Cell.individual-Endodermis.Total -1.855081e+05 -503962.9
## Endodermis.Cell.Individual-Endodermis.Total -1.875252e+05 -517028.0
## Epidermis.Cell.Individual-Vasculature.Total -3.641813e+05 -682636.1
## Cortex.Cell.individual-Vasculature.Total -3.641932e+05 -682648.1
## Endodermis.Cell.Individual-Vasculature.Total -3.662103e+05 -695713.1
## Cortex.Cell.individual-Epidermis.Cell.Individual -1.196429e+01 -189202.3
## Endodermis.Cell.Individual-Epidermis.Cell.Individual -2.029071e+03 -209276.7
## Endodermis.Cell.Individual-Cortex.Cell.individual -2.017107e+03 -209264.8
## upr p adj
## Epidermis.Total-Root.Area -759715.54 1.215886e-10
## Cortex.Total-Root.Area -646708.41 1.474936e-10
## Endodermis.Total-Root.Area -1052866.24 1.214566e-10
## Vasculature.Total-Root.Area -874181.07 1.215006e-10
## Epidermis.Cell.Individual-Root.Area -1333057.26 1.214271e-10
## Cortex.Cell.individual-Root.Area -1333069.22 1.214271e-10
## Endodermis.Cell.Individual-Root.Area -1323351.07 1.214271e-10
## Cortex.Total-Epidermis.Total 491387.88 9.944054e-01
## Endodermis.Total-Epidermis.Total 85230.04 2.405053e-01
## Vasculature.Total-Epidermis.Total 263915.21 9.701517e-01
## Epidermis.Cell.Individual-Epidermis.Total -194960.97 4.090016e-05
## Cortex.Cell.individual-Epidermis.Total -194972.94 4.087914e-05
## Endodermis.Cell.Individual-Epidermis.Total -185254.78 8.320813e-05
## Endodermis.Total-Cortex.Total 2540.08 5.267175e-02
## Vasculature.Total-Cortex.Total 181225.25 6.722425e-01
## Epidermis.Cell.Individual-Cortex.Total -273199.08 2.643401e-06
## Cortex.Cell.individual-Cortex.Total -273211.04 2.642042e-06
## Endodermis.Cell.Individual-Cortex.Total -264180.21 5.667116e-06
## Vasculature.Total-Endodermis.Total 587383.08 8.755543e-01
## Epidermis.Cell.Individual-Endodermis.Total 132958.75 6.192698e-01
## Cortex.Cell.individual-Endodermis.Total 132946.79 6.191920e-01
## Endodermis.Cell.Individual-Endodermis.Total 141977.62 6.468064e-01
## Epidermis.Cell.Individual-Vasculature.Total -45726.41 1.359818e-02
## Cortex.Cell.individual-Vasculature.Total -45738.38 1.359323e-02
## Endodermis.Cell.Individual-Vasculature.Total -36707.54 1.849721e-02
## Cortex.Cell.individual-Epidermis.Cell.Individual 189178.41 1.000000e+00
## Endodermis.Cell.Individual-Epidermis.Cell.Individual 205218.60 1.000000e+00
## Endodermis.Cell.Individual-Cortex.Cell.individual 205230.56 1.000000e+00P7 = Output$variable[,'p adj']
stat.test<- multcompLetters(P7)
testd <- as.data.frame(stat.test$Letters)
testd$group2 <- rownames(testd)
testd$group1 <- rownames(testd)
testd$variable <- rownames(testd)
testd$variable <- rownames(testd)
colnames(testd)[1] <- "Tukey"
testd$Folder.Path <- "MR_Mid"
testdOutput <- TukeyHSD(aov(value ~ variable, data = LR_Proximal))
Output$variable## diff lwr
## Epidermis.Total-Root.Area -603864.00 -626932.92
## Cortex.Total-Root.Area -697886.00 -720954.92
## Endodermis.Total-Root.Area -973424.00 -996492.92
## Vasculature.Total-Root.Area -810200.00 -833268.92
## Epidermis.Cell.Individual-Root.Area -1020067.00 -1038304.58
## Cortex.Cell.individual-Root.Area -1020628.25 -1038865.83
## Endodermis.Cell.Individual-Root.Area -1023210.25 -1041447.83
## Cortex.Total-Epidermis.Total -94022.00 -117090.92
## Endodermis.Total-Epidermis.Total -369560.00 -392628.92
## Vasculature.Total-Epidermis.Total -206336.00 -229404.92
## Epidermis.Cell.Individual-Epidermis.Total -416203.00 -434440.58
## Cortex.Cell.individual-Epidermis.Total -416764.25 -435001.83
## Endodermis.Cell.Individual-Epidermis.Total -419346.25 -437583.83
## Endodermis.Total-Cortex.Total -275538.00 -298606.92
## Vasculature.Total-Cortex.Total -112314.00 -135382.92
## Epidermis.Cell.Individual-Cortex.Total -322181.00 -340418.58
## Cortex.Cell.individual-Cortex.Total -322742.25 -340979.83
## Endodermis.Cell.Individual-Cortex.Total -325324.25 -343561.83
## Vasculature.Total-Endodermis.Total 163224.00 140155.08
## Epidermis.Cell.Individual-Endodermis.Total -46643.00 -64880.58
## Cortex.Cell.individual-Endodermis.Total -47204.25 -65441.83
## Endodermis.Cell.Individual-Endodermis.Total -49786.25 -68023.83
## Epidermis.Cell.Individual-Vasculature.Total -209867.00 -228104.58
## Cortex.Cell.individual-Vasculature.Total -210428.25 -228665.83
## Endodermis.Cell.Individual-Vasculature.Total -213010.25 -231247.83
## Cortex.Cell.individual-Epidermis.Cell.Individual -561.25 -12095.71
## Endodermis.Cell.Individual-Epidermis.Cell.Individual -3143.25 -14677.71
## Endodermis.Cell.Individual-Cortex.Cell.individual -2582.00 -14116.46
## upr p adj
## Epidermis.Total-Root.Area -580795.085 5.449526e-10
## Cortex.Total-Root.Area -674817.085 5.449526e-10
## Endodermis.Total-Root.Area -950355.085 5.449526e-10
## Vasculature.Total-Root.Area -787131.085 5.449526e-10
## Epidermis.Cell.Individual-Root.Area -1001829.421 5.449526e-10
## Cortex.Cell.individual-Root.Area -1002390.671 5.449526e-10
## Endodermis.Cell.Individual-Root.Area -1004972.671 5.449526e-10
## Cortex.Total-Epidermis.Total -70953.085 1.396213e-06
## Endodermis.Total-Epidermis.Total -346491.085 5.471159e-10
## Vasculature.Total-Epidermis.Total -183267.085 2.639739e-09
## Epidermis.Cell.Individual-Epidermis.Total -397965.421 5.449526e-10
## Cortex.Cell.individual-Epidermis.Total -398526.671 5.449526e-10
## Endodermis.Cell.Individual-Epidermis.Total -401108.671 5.449526e-10
## Endodermis.Total-Cortex.Total -252469.085 7.491844e-10
## Vasculature.Total-Cortex.Total -89245.085 3.019059e-07
## Epidermis.Cell.Individual-Cortex.Total -303943.421 5.451838e-10
## Cortex.Cell.individual-Cortex.Total -304504.671 5.451738e-10
## Endodermis.Cell.Individual-Cortex.Total -307086.671 5.451332e-10
## Vasculature.Total-Endodermis.Total 186292.915 7.070043e-09
## Epidermis.Cell.Individual-Endodermis.Total -28405.421 6.892572e-05
## Cortex.Cell.individual-Endodermis.Total -28966.671 6.248189e-05
## Endodermis.Cell.Individual-Endodermis.Total -31548.671 4.024712e-05
## Epidermis.Cell.Individual-Vasculature.Total -191629.421 8.486766e-10
## Cortex.Cell.individual-Vasculature.Total -192190.671 8.404826e-10
## Endodermis.Cell.Individual-Vasculature.Total -194772.671 8.052287e-10
## Cortex.Cell.individual-Epidermis.Cell.Individual 10973.208 9.999991e-01
## Endodermis.Cell.Individual-Epidermis.Cell.Individual 8391.208 9.537219e-01
## Endodermis.Cell.Individual-Cortex.Cell.individual 8952.458 9.831754e-01P7 = Output$variable[,'p adj']
stat.test<- multcompLetters(P7)
teste <- as.data.frame(stat.test$Letters)
teste$group2 <- rownames(teste)
teste$group1 <- rownames(teste)
teste$variable <- rownames(teste)
teste$variable <- rownames(teste)
colnames(teste)[1] <- "Tukey"
teste$Folder.Path <- "MR_Proximal"
testetest <- rbind(testc, testd, teste)
testAllArea <- AllArea + stat_pvalue_manual(test, label = "Tukey", y.position = 2000000)
AllArea## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Removed 106 rows containing missing values or values outside the scale range
## (`geom_point()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_segment()`).
pdf("Area_All_facet_per_Root_segment-new.pdf", height = 15, width = 7)
plot(AllArea)## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Removed 106 rows containing missing values or values outside the scale range
## (`geom_point()`).## Warning: Removed 5 rows containing missing values or values outside the scale range
## (`geom_segment()`).dev.off()## quartz_off_screen
## 2OK - let’s try another way to plot this:
AllArea2 <- ggerrorplot(data_melt2, x = "Folder.Path", y = "value", color = "Folder.Path", fill = "Folder.Path",
desc_stat = "mean_sd", add = "jitter", facet.by = "variable", scales="free", ncol = 5,
xlab="", ylab= "Area (a.u.)", add.params = list(color = "darkgray")) + color_palette("aaas")
AllArea2 <- AllArea2 + stat_compare_means(method = "aov")
AllArea2 <- AllArea2 + stat_compare_means(comparisons = my_comparisons)
AllArea2 <- AllArea2 + rremove("legend") + theme(axis.text.x = element_text(angle = 90, vjust = 0.5, hjust=1))
AllArea2## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Computation failed in `stat_compare_means()`.
## Caused by error in `contrasts<-`:
## ! contrasts can be applied only to factors with 2 or more levels## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 106 rows containing missing values or values outside the scale range
## (`geom_point()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
pdf("Area_All_facet_within_Root_segment-new.pdf", height = 7, width = 10)
plot(AllArea2)## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_summary()`).## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_compare_means()`).## Warning: Computation failed in `stat_compare_means()`.
## Caused by error in `contrasts<-`:
## ! contrasts can be applied only to factors with 2 or more levels## Warning: Removed 106 rows containing non-finite outside the scale range
## (`stat_signif()`).## Warning: Removed 106 rows containing missing values or values outside the scale range
## (`geom_point()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_segment()`).dev.off()## quartz_off_screen
## 2