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library(pheatmap)
library(EnhancedVolcano)
library(tidyverse)
library(dplyr)
#dir.create('BIN1.DEPS.Analysis')
#setwd('/Users/usri/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis/')
#cleanDat.norm.After.normalization <- readRDS("~/Desktop/BV2.Human.Microglia.BIN1/cleanDat.norm.After.normalization.rds")
BIN1_cleanDat_norm_After_normalization_with_GENEs_unique <- read.csv("BIN1_cleanDat_norm_After_normalization_with_GENEs.unique.csv", row.names = 1)
cleanDat.norm.After.normalization <- BIN1_cleanDat_norm_After_normalization_with_GENEs_unique
boxplot(cleanDat.norm.After.normalization)
library(readr)
#load metadata files group wise
case1.KO.Vehicle.vs.Cytokine <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/case1.KO.Vehicle.vs.Cytokine.rds")
head(case1.KO.Vehicle.vs.Cytokine)
## Condition Groups Genotype Group
## Intensity.112_Kumar_C20_3 KO.NES.vehicle Group1 KO.NES.vehicle KO
## Intensity.116_Kumar_C20_4 KO.NES.cytokines Group1 KO.NES.cytokines KO
## Intensity.172_Kumar_C20_11 KO.NES.vehicle Group2 KO.NES.vehicle KO
## Intensity.050_Kumar_C20_12 KO.NES.cytokines Group2 KO.NES.cytokines KO
## Intensity.164_Kumar_C20_19 KO.NES.vehicle Group3 KO.NES.vehicle KO
## Intensity.180_Kumar_C20_20 KO.NES.cytokines Group3 KO.NES.cytokines KO
case2.WT.Vehicle.vs.Cytokines <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/case2.WT.Vehicle.vs.Cytokines.rds")
head(case2.WT.Vehicle.vs.Cytokines)
## Condition Groups Genotype
## Intensity.136_Kumar_C20_1 WT.NES.vehicle Group1 WT.NES.vehicle
## Intensity.176_Kumar_C20_2 WT.NES.cytokines Group1 WT.NES.cytokines
## Intensity.204_Kumar_C20_9 WT.NES.vehicle Group2 WT.NES.vehicle
## Intensity.156_Kumar_C20_10 WT.NES.cytokines Group2 WT.NES.cytokines
## Intensity.200_Kumar_C20_17 WT.NES.vehicle Group3 WT.NES.vehicle
## Intensity.168_Kumar_C20_18 WT.NES.cytokines Group3 WT.NES.cytokines
case3.WT.vs.KO.Cytokines <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/case3.WT.vs.KO.Cytokines.rds")
head(case3.WT.vs.KO.Cytokines)
## Condition Groups Genotype
## Intensity.176_Kumar_C20_2 WT.NES.cytokines Group1 WT.NES.cytokines
## Intensity.116_Kumar_C20_4 KO.NES.cytokines Group1 KO.NES.cytokines
## Intensity.156_Kumar_C20_10 WT.NES.cytokines Group2 WT.NES.cytokines
## Intensity.050_Kumar_C20_12 KO.NES.cytokines Group2 KO.NES.cytokines
## Intensity.168_Kumar_C20_18 WT.NES.cytokines Group3 WT.NES.cytokines
## Intensity.180_Kumar_C20_20 KO.NES.cytokines Group3 KO.NES.cytokines
case4.WT.versus.KO.Vehicles <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/case4.WT.versus.KO.Vehicles.rds")
head(case4.WT.versus.KO.Vehicles)
## Condition Groups Genotype
## Intensity.136_Kumar_C20_1 WT.NES.vehicle Group1 WT.NES.vehicle
## Intensity.112_Kumar_C20_3 KO.NES.vehicle Group1 KO.NES.vehicle
## Intensity.204_Kumar_C20_9 WT.NES.vehicle Group2 WT.NES.vehicle
## Intensity.172_Kumar_C20_11 KO.NES.vehicle Group2 KO.NES.vehicle
## Intensity.200_Kumar_C20_17 WT.NES.vehicle Group3 WT.NES.vehicle
## Intensity.164_Kumar_C20_19 KO.NES.vehicle Group3 KO.NES.vehicle
case5.WT.versus.KO <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/case5.WT.versus.KO.rds")
head(case5.WT.versus.KO)
## Condition Groups Genotype Group
## Intensity.136_Kumar_C20_1 WT.NES.vehicle Group1 WT.NES.vehicle WT
## Intensity.176_Kumar_C20_2 WT.NES.cytokines Group1 WT.NES.cytokines WT
## Intensity.112_Kumar_C20_3 KO.NES.vehicle Group1 KO.NES.vehicle KO
## Intensity.116_Kumar_C20_4 KO.NES.cytokines Group1 KO.NES.cytokines KO
## Intensity.204_Kumar_C20_9 WT.NES.vehicle Group2 WT.NES.vehicle WT
## Intensity.156_Kumar_C20_10 WT.NES.cytokines Group2 WT.NES.cytokines WT
#making of cleanDat based on samples in metadta files for comaprisions
##case1.KO.Vehicle.vs.Cytokine
samples_to_subset <- row.names(case1.KO.Vehicle.vs.Cytokine)
# Subsetting the matrix based on the selected samples
subset_matrix <- cleanDat.norm.After.normalization[, colnames(cleanDat.norm.After.normalization) %in% samples_to_subset]
head(subset_matrix, 2)
## Intensity.112_Kumar_C20_3 Intensity.116_Kumar_C20_4
## LOC100507462 24.27651 25.49742
## UBA6 26.42183 26.68525
## Intensity.172_Kumar_C20_11 Intensity.050_Kumar_C20_12
## LOC100507462 25.85425 25.78600
## UBA6 26.16788 26.47889
## Intensity.164_Kumar_C20_19 Intensity.180_Kumar_C20_20
## LOC100507462 26.21295 25.80621
## UBA6 26.28645 26.69676
## Intensity.148_Kumar_C20_27 Intensity.196_Kumar_C20_28
## LOC100507462 25.89553 25.49484
## UBA6 26.13427 26.35224
## Intensity.074_Kumar_C20_35 Intensity.078_Kumar_C20_36
## LOC100507462 25.55518 25.27947
## UBA6 26.42775 26.47712
colnames(subset_matrix) == row.names(case1.KO.Vehicle.vs.Cytokine)
## [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
saveRDS(subset_matrix, file = 'case1.cleanDat.KO.Vehicle.vs.Cytokine.rds')
###case2.WT.Vehicle.vs.Cytokines
samples_to_subset <- row.names(case2.WT.Vehicle.vs.Cytokines)
# Subsetting the matrix based on the selected samples
subset_matrix <- cleanDat.norm.After.normalization[, colnames(cleanDat.norm.After.normalization) %in% samples_to_subset]
head(subset_matrix, 2)
## Intensity.176_Kumar_C20_2 Intensity.204_Kumar_C20_9
## LOC100507462 25.3547 25.50994
## UBA6 27.2039 26.90907
## Intensity.156_Kumar_C20_10 Intensity.200_Kumar_C20_17
## LOC100507462 25.55066 25.31509
## UBA6 26.71910 26.85774
## Intensity.168_Kumar_C20_18 Intensity.082_Kumar_C20_25
## LOC100507462 25.40830 25.07928
## UBA6 26.84887 26.96015
## Intensity.220_Kumar_C20_26 Intensity.086_Kumar_C20_33
## LOC100507462 25.60928 25.34336
## UBA6 27.13333 26.90907
## Intensity.160_Kumar_C20_34
## LOC100507462 24.94545
## UBA6 26.84887
colnames(subset_matrix) == row.names(case2.WT.Vehicle.vs.Cytokines)
## Warning in colnames(subset_matrix) == row.names(case2.WT.Vehicle.vs.Cytokines):
## longer object length is not a multiple of shorter object length
## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
saveRDS(subset_matrix, file = 'case2.cleanDat.WT.Vehicle.vs.Cytokines.rds')
##case3.WT.vs.KO.Cytokines
samples_to_subset <- row.names(case3.WT.vs.KO.Cytokines)
# Subsetting the matrix based on the selected samples
subset_matrix <- cleanDat.norm.After.normalization[, colnames(cleanDat.norm.After.normalization) %in% samples_to_subset]
head(subset_matrix, 2)
## Intensity.176_Kumar_C20_2 Intensity.116_Kumar_C20_4
## LOC100507462 25.3547 25.49742
## UBA6 27.2039 26.68525
## Intensity.156_Kumar_C20_10 Intensity.050_Kumar_C20_12
## LOC100507462 25.55066 25.78600
## UBA6 26.71910 26.47889
## Intensity.168_Kumar_C20_18 Intensity.180_Kumar_C20_20
## LOC100507462 25.40830 25.80621
## UBA6 26.84887 26.69676
## Intensity.220_Kumar_C20_26 Intensity.196_Kumar_C20_28
## LOC100507462 25.60928 25.49484
## UBA6 27.13333 26.35224
## Intensity.160_Kumar_C20_34 Intensity.078_Kumar_C20_36
## LOC100507462 24.94545 25.27947
## UBA6 26.84887 26.47712
colnames(subset_matrix) == row.names(case3.WT.vs.KO.Cytokines)
## [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
saveRDS(subset_matrix, file = 'case3.cleanDat.WT.vs.KO.Cytokines.rds')
##case4.WT.versus.KO.Vehicles
samples_to_subset <- row.names(case4.WT.versus.KO.Vehicles)
# Subsetting the matrix based on the selected samples
subset_matrix <- cleanDat.norm.After.normalization[, colnames(cleanDat.norm.After.normalization) %in% samples_to_subset]
head(subset_matrix, 2)
## Intensity.112_Kumar_C20_3 Intensity.204_Kumar_C20_9
## LOC100507462 24.27651 25.50994
## UBA6 26.42183 26.90907
## Intensity.172_Kumar_C20_11 Intensity.200_Kumar_C20_17
## LOC100507462 25.85425 25.31509
## UBA6 26.16788 26.85774
## Intensity.164_Kumar_C20_19 Intensity.082_Kumar_C20_25
## LOC100507462 26.21295 25.07928
## UBA6 26.28645 26.96015
## Intensity.148_Kumar_C20_27 Intensity.086_Kumar_C20_33
## LOC100507462 25.89553 25.34336
## UBA6 26.13427 26.90907
## Intensity.074_Kumar_C20_35
## LOC100507462 25.55518
## UBA6 26.42775
colnames(subset_matrix) == row.names(case4.WT.versus.KO.Vehicles)
## Warning in colnames(subset_matrix) == row.names(case4.WT.versus.KO.Vehicles):
## longer object length is not a multiple of shorter object length
## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
saveRDS(subset_matrix, file = 'case4.cleanDat.WT.versus.KO.Vehicles.rds')
##case5.WT.versus.KO
samples_to_subset <- row.names(case5.WT.versus.KO)
# Subsetting the matrix based on the selected samples
subset_matrix <- cleanDat.norm.After.normalization[, colnames(cleanDat.norm.After.normalization) %in% samples_to_subset]
head(subset_matrix, 2)
## Intensity.176_Kumar_C20_2 Intensity.112_Kumar_C20_3
## LOC100507462 25.3547 24.27651
## UBA6 27.2039 26.42183
## Intensity.116_Kumar_C20_4 Intensity.204_Kumar_C20_9
## LOC100507462 25.49742 25.50994
## UBA6 26.68525 26.90907
## Intensity.156_Kumar_C20_10 Intensity.172_Kumar_C20_11
## LOC100507462 25.55066 25.85425
## UBA6 26.71910 26.16788
## Intensity.050_Kumar_C20_12 Intensity.200_Kumar_C20_17
## LOC100507462 25.78600 25.31509
## UBA6 26.47889 26.85774
## Intensity.168_Kumar_C20_18 Intensity.164_Kumar_C20_19
## LOC100507462 25.40830 26.21295
## UBA6 26.84887 26.28645
## Intensity.180_Kumar_C20_20 Intensity.082_Kumar_C20_25
## LOC100507462 25.80621 25.07928
## UBA6 26.69676 26.96015
## Intensity.220_Kumar_C20_26 Intensity.148_Kumar_C20_27
## LOC100507462 25.60928 25.89553
## UBA6 27.13333 26.13427
## Intensity.196_Kumar_C20_28 Intensity.086_Kumar_C20_33
## LOC100507462 25.49484 25.34336
## UBA6 26.35224 26.90907
## Intensity.160_Kumar_C20_34 Intensity.074_Kumar_C20_35
## LOC100507462 24.94545 25.55518
## UBA6 26.84887 26.42775
## Intensity.078_Kumar_C20_36
## LOC100507462 25.27947
## UBA6 26.47712
colnames(subset_matrix) == row.names(case5.WT.versus.KO)
## Warning in colnames(subset_matrix) == row.names(case5.WT.versus.KO): longer
## object length is not a multiple of shorter object length
## [1] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
## [13] FALSE FALSE FALSE FALSE FALSE FALSE FALSE FALSE
saveRDS(subset_matrix, file = 'case5.cleanDat.WT.versus.KO.rds')
case1.cleanDat.KO.Vehicle.vs.Cytokine <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis/case1.cleanDat.KO.Vehicle.vs.Cytokine.rds")
cleanDat <- case1.cleanDat.KO.Vehicle.vs.Cytokine
numericMeta <- case1.KO.Vehicle.vs.Cytokine
condition <- case1.KO.Vehicle.vs.Cytokine$Genotype
Grouping <- case1.KO.Vehicle.vs.Cytokine$Genotype
source("/Users/usri/Desktop/Screen/parANOVA.dex.R")
ANOVAout <- parANOVA.dex()
## - parallelThreads variable not set. Running with 2 threads only.
## - Network color assignment vector not supplied or not of length in rows of cleanDat; will not be included in output table and data frame.
## - twoGroupCorrMethod variable not set to a correction method for p.adjust when only 2 groups of samples specified in Grouping. Using Benjamini Hochberg 'BH' FDR.
## - fallbackIfSmallTukeyP variable not set. Using recommended Bonferroni t-test FDR for unreliable Tukey p values <10^-8.5
##
## Attaching package: 'foreach'
## The following objects are masked from 'package:purrr':
##
## accumulate, when
##
## ...Tukey p<10^-8.5 Fallback calculations using Bonferroni corrected T test: 0 [0%]
labelTop <- 10
FCmin= 0
flip = 3
signifP=0.05
plotVolc()
## - No comparison p value columns selected in selectComps. Using ALL comparisons.
## - selectComps may not reference valid integer p value column indexes of ANOVAout (or CORout).
## Output will be for all comparisons or correlation(s).
## - useNETcolors not set or not TRUE/FALSE. NETcolors not found in ANOVAout, so 3 color volcano(es) will be drawn.
## - Variable outputfigs not specified. Saving volcano plots to /Users/usri/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis .
##
## ...Thresholds:
## [x] Applying a 0% minimum fold change threshold at + and - x=0 .
## [y] with minimum significance cutoff p < 0.05, equivalent to -log10(p) y=1.3 .
##
## Processing ANOVA column 3 (KO.NES.cytokines vs KO.NES.vehicle) for volcano ...
## Warning: Using `size` aesthetic for lines was deprecated in ggplot2 3.4.0.
## ℹ Please use `linewidth` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
## Generating PDF volcano for ANOVAout column 3 (KO.NES.cytokines vs KO.NES.vehicle) ...
## Generating HTML volcano for ANOVAout column 3 (KO.NES.cytokines vs KO.NES.vehicle) ...
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
case2.cleanDat.WT.Vehicle.vs.Cytokines <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis/case2.cleanDat.WT.Vehicle.vs.Cytokines.rds")
cleanDat <- case2.cleanDat.WT.Vehicle.vs.Cytokines
numericMeta <- case2.WT.Vehicle.vs.Cytokines
condition <- case2.WT.Vehicle.vs.Cytokines$Genotype
Grouping <- case2.WT.Vehicle.vs.Cytokines$Genotype
table(case2.WT.Vehicle.vs.Cytokines$Genotype)
##
## WT.NES.cytokines WT.NES.vehicle
## 5 5
source("/Users/usri/Desktop/Screen/parANOVA.dex.R")
ANOVAout <- parANOVA.dex()
## - parallelThreads variable not set. Running with 2 threads only.
## - Network color assignment vector not supplied or not of length in rows of cleanDat; will not be included in output table and data frame.
## - twoGroupCorrMethod variable not set to a correction method for p.adjust when only 2 groups of samples specified in Grouping. Using Benjamini Hochberg 'BH' FDR.
## - fallbackIfSmallTukeyP variable not set. Using recommended Bonferroni t-test FDR for unreliable Tukey p values <10^-8.5
## Warning in cbind(...): number of rows of result is not a multiple of vector
## length (arg 2)
##
## ...Tukey p<10^-8.5 Fallback calculations using Bonferroni corrected T test: 1 [0.027%]
labelTop <- 10
FCmin= 0
flip = 3
signifP=0.05
plotVolc()
## - No comparison p value columns selected in selectComps. Using ALL comparisons.
## - selectComps may not reference valid integer p value column indexes of ANOVAout (or CORout).
## Output will be for all comparisons or correlation(s).
## - useNETcolors not set or not TRUE/FALSE. NETcolors not found in ANOVAout, so 3 color volcano(es) will be drawn.
## - Variable outputfigs not specified. Saving volcano plots to /Users/usri/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis .
##
## ...Thresholds:
## [x] Applying a 0% minimum fold change threshold at + and - x=0 .
## [y] with minimum significance cutoff p < 0.05, equivalent to -log10(p) y=1.3 .
##
## Processing ANOVA column 3 (WT.NES.cytokines vs WT.NES.vehicle) for volcano ...
## Generating PDF volcano for ANOVAout column 3 (WT.NES.cytokines vs WT.NES.vehicle) ...
## Generating HTML volcano for ANOVAout column 3 (WT.NES.cytokines vs WT.NES.vehicle) ...
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
case3.cleanDat.WT.vs.KO.Cytokines <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis/case3.cleanDat.WT.vs.KO.Cytokines.rds")
cleanDat <- case3.cleanDat.WT.vs.KO.Cytokines
numericMeta <- case3.WT.vs.KO.Cytokines
condition <- case3.WT.vs.KO.Cytokines$Genotype
Grouping <- case3.WT.vs.KO.Cytokines$Genotype
source("/Users/usri/Desktop/Screen/parANOVA.dex.R")
ANOVAout <- parANOVA.dex()
## - parallelThreads variable not set. Running with 2 threads only.
## - Network color assignment vector not supplied or not of length in rows of cleanDat; will not be included in output table and data frame.
## - twoGroupCorrMethod variable not set to a correction method for p.adjust when only 2 groups of samples specified in Grouping. Using Benjamini Hochberg 'BH' FDR.
## - fallbackIfSmallTukeyP variable not set. Using recommended Bonferroni t-test FDR for unreliable Tukey p values <10^-8.5
##
## ...Tukey p<10^-8.5 Fallback calculations using Bonferroni corrected T test: 4 [0.11%]
labelTop <- 10
FCmin= 0
flip = -3
signifP=0.05
plotVolc()
## - No comparison p value columns selected in selectComps. Using ALL comparisons.
## - selectComps may not reference valid integer p value column indexes of ANOVAout (or CORout).
## Output will be for all comparisons or correlation(s).
## - useNETcolors not set or not TRUE/FALSE. NETcolors not found in ANOVAout, so 3 color volcano(es) will be drawn.
## - Variable outputfigs not specified. Saving volcano plots to /Users/usri/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis .
##
## ...Thresholds:
## [x] Applying a 0% minimum fold change threshold at + and - x=0 .
## [y] with minimum significance cutoff p < 0.05, equivalent to -log10(p) y=1.3 .
##
## Processing ANOVA column 3 (WT.NES.cytokines vs KO.NES.cytokines) for volcano ...
## Generating PDF volcano for ANOVAout column 3 (WT.NES.cytokines vs KO.NES.cytokines) ...
## Generating HTML volcano for ANOVAout column 3 (WT.NES.cytokines vs KO.NES.cytokines) ...
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
case4.cleanDat.WT.versus.KO.Vehicles <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis/case4.cleanDat.WT.versus.KO.Vehicles.rds")
cleanDat <- case4.cleanDat.WT.versus.KO.Vehicles
numericMeta <- case4.WT.versus.KO.Vehicles
condition <- case4.WT.versus.KO.Vehicles$Genotype
Grouping <- case4.WT.versus.KO.Vehicles$Genotype
source("/Users/usri/Desktop/Screen/parANOVA.dex.R")
ANOVAout <- parANOVA.dex()
## - parallelThreads variable not set. Running with 2 threads only.
## - Network color assignment vector not supplied or not of length in rows of cleanDat; will not be included in output table and data frame.
## - twoGroupCorrMethod variable not set to a correction method for p.adjust when only 2 groups of samples specified in Grouping. Using Benjamini Hochberg 'BH' FDR.
## - fallbackIfSmallTukeyP variable not set. Using recommended Bonferroni t-test FDR for unreliable Tukey p values <10^-8.5
## Warning in cbind(...): number of rows of result is not a multiple of vector
## length (arg 2)
##
## ...Tukey p<10^-8.5 Fallback calculations using Bonferroni corrected T test: 2 [0.054%]
labelTop <- 10
FCmin= 0
flip = -3
signifP=0.05
plotVolc()
## - No comparison p value columns selected in selectComps. Using ALL comparisons.
## - selectComps may not reference valid integer p value column indexes of ANOVAout (or CORout).
## Output will be for all comparisons or correlation(s).
## - useNETcolors not set or not TRUE/FALSE. NETcolors not found in ANOVAout, so 3 color volcano(es) will be drawn.
## - Variable outputfigs not specified. Saving volcano plots to /Users/usri/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis .
##
## ...Thresholds:
## [x] Applying a 0% minimum fold change threshold at + and - x=0 .
## [y] with minimum significance cutoff p < 0.05, equivalent to -log10(p) y=1.3 .
##
## Processing ANOVA column 3 (WT.NES.vehicle vs KO.NES.vehicle) for volcano ...
## Generating PDF volcano for ANOVAout column 3 (WT.NES.vehicle vs KO.NES.vehicle) ...
## Generating HTML volcano for ANOVAout column 3 (WT.NES.vehicle vs KO.NES.vehicle) ...
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
case5.cleanDat.WT.versus.KO <- readRDS("~/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis/case5.cleanDat.WT.versus.KO.rds")
cleanDat <- case5.cleanDat.WT.versus.KO
numericMeta <- case5.WT.versus.KO$Group
condition <- case5.WT.versus.KO$Group
Grouping <- case5.WT.versus.KO$Group
source("/Users/usri/Desktop/Screen/parANOVA.dex.R")
ANOVAout <- parANOVA.dex()
## - parallelThreads variable not set. Running with 2 threads only.
## - Network color assignment vector not supplied or not of length in rows of cleanDat; will not be included in output table and data frame.
## - twoGroupCorrMethod variable not set to a correction method for p.adjust when only 2 groups of samples specified in Grouping. Using Benjamini Hochberg 'BH' FDR.
## - fallbackIfSmallTukeyP variable not set. Using recommended Bonferroni t-test FDR for unreliable Tukey p values <10^-8.5
## Warning in cbind(...): number of rows of result is not a multiple of vector
## length (arg 2)
##
## ...Tukey p<10^-8.5 Fallback calculations using Bonferroni corrected T test: 0 [0%]
labelTop <- 10
FCmin= 0
flip = -3
signifP=0.05
plotVolc()
## - No comparison p value columns selected in selectComps. Using ALL comparisons.
## - selectComps may not reference valid integer p value column indexes of ANOVAout (or CORout).
## Output will be for all comparisons or correlation(s).
## - useNETcolors not set or not TRUE/FALSE. NETcolors not found in ANOVAout, so 3 color volcano(es) will be drawn.
## - Variable outputfigs not specified. Saving volcano plots to /Users/usri/Desktop/BIN1.DEPs.analysis.Aug20.24/BIN1.DEPS.Analysis .
##
## ...Thresholds:
## [x] Applying a 0% minimum fold change threshold at + and - x=0 .
## [y] with minimum significance cutoff p < 0.05, equivalent to -log10(p) y=1.3 .
##
## Processing ANOVA column 3 (WT vs KO) for volcano ...
## Generating PDF volcano for ANOVAout column 3 (WT vs KO) ...
## Generating HTML volcano for ANOVAout column 3 (WT vs KO) ...
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
## Warning in geom2trace.default(dots[[1L]][[3L]], dots[[2L]][[1L]], dots[[3L]][[1L]]): geom_GeomLabelRepel() has yet to be implemented in plotly.
## If you'd like to see this geom implemented,
## Please open an issue with your example code at
## https://github.com/ropensci/plotly/issues
