This dataset contains nine tissues (heart, hippocampus, hypothalamus, kidney, liver, prefrontal cortex, skeletal muscle, small intestine, and spleen) from C57BL/6J mice that were fed 2-deoxyglucose (6g/L) through their drinking water for 96hrs or 4wks. 96hr mice were given their 2DG treatment 2 weeks after the other cohort started the 4 week treatment. The organs from the mice were harvested and processed for metabolomics and transcriptomics. The data in this document pertains to the transcriptomics data only. The counts that were used were FPKM normalized before being log transformed. It was determined that sample A113 had low RNAseq quality and through further analyses with PCA, MA plots, and clustering was an outlier and will be removed for the rest of the analyses performed. This document will look at modules that were significantly correlated with traits and had pathways identified within the WGCNA. Those modules will be assessed to see which modules from other tissues and their modules significantly overlapped.
needed.packages <- c("tidyverse", "here", "functional", "gplots", "dplyr", "GeneOverlap", "R.utils", "reshape2","magrittr","data.table", "RColorBrewer","preprocessCore", "ARTool","emmeans", "phia", "gprofiler2", "rlist")
for(i in 1:length(needed.packages)){library(needed.packages[i], character.only = TRUE)}
source(here("source_files","WGCNA_source.R"))Matched<-readRDS(here("Data","Chang_2DG_BL6_Matched_annotation_intersection_modules.RData"))Each tissue module was compared to the traits in the experiment. The modules that were significantly correlated for a trait were then compared within the jaccard index across all other tissues. The significant overlaps were then summarized to determine which pathways were most common. Below are the pathway lists and their frequency for each module within a tissue that was also correlated to a trait and their frequency bar plots.
genes.heart.darkgreen <- genes.jaccard.pathways(Matched, "Heart_darkgreen")if(is.null(genes.heart.darkgreen)) {
print("No significant pathways")
} else {genes.heart.darkgreen <- genes.heart.darkgreen$result
DT.table.jaccard(genes.heart.darkgreen[c(11,4:6,3)])
}genes.heart.darkgrey <- genes.jaccard.pathways(Matched, "Heart_darkgrey")if(is.null(genes.heart.darkgrey)) {
print("No significant pathways")
} else {genes.heart.darkgrey <- genes.heart.darkgrey$result
DT.table.jaccard(genes.heart.darkgrey[c(11,4:6,3)])
}genes.heart.darkorange <- genes.jaccard.pathways(Matched, "Heart_darkorange")if(is.null(genes.heart.darkorange)) {
print("No significant pathways")
} else {genes.heart.darkorange <- genes.heart.darkorange$result
DT.table.jaccard(genes.heart.darkorange[c(11,4:6,3)])
}## [1] "No significant pathways"Server won’t run this module currently
#genes.heart.plum1 <- genes.jaccard.pathways(Matched, "Heart_plum1")# if(is.null(genes.heart.plum1)) {
# print("No significant pathways")
# } else {genes.heart.plum1 <- genes.heart.plum1$result
# DT.table.jaccard(genes.heart.plum1[c(11,4:6,3)])
#
# }genes.hippocampus.green <- genes.jaccard.pathways(Matched, "Hippocampus_green")if(is.null(genes.hippocampus.green)) {
print("No significant pathways")
} else {genes.hippocampus.green <- genes.hippocampus.green$result
DT.table.jaccard(genes.hippocampus.green[c(11,4:6,3)])
}genes.hippocampus.coral1 <- genes.jaccard.pathways(Matched, "Hippocampus_coral1")if(is.null(genes.hippocampus.coral1)) {
print("No significant pathways")
} else {genes.hippocampus.coral1 <- genes.hippocampus.coral1$result
DT.table.jaccard(genes.hippocampus.coral1[c(11,4:6,3)])
}genes.hippocampus.darkslateblue <- genes.jaccard.pathways(Matched, "Hippocampus_darkslateblue")if(is.null(genes.hippocampus.darkslateblue)) {
print("No significant pathways")
} else {genes.hippocampus.darkslateblue <- genes.hippocampus.darkslateblue$result
DT.table.jaccard(genes.hippocampus.darkslateblue[c(11,4:6,3)])
}genes.hippocampus.darkolivegreen <- genes.jaccard.pathways(Matched, "Hippocampus_darkolivegreen")if(is.null(genes.hippocampus.darkolivegreen)) {
print("No significant pathways")
} else {genes.hippocampus.darkolivegreen <- genes.hippocampus.darkolivegreen$result
DT.table.jaccard(genes.hippocampus.darkolivegreen[c(11,4:6,3)])
}## [1] "No significant pathways"genes.hippocampus.khaki3 <- genes.jaccard.pathways(Matched, "Hippocampus_khaki3")if(is.null(genes.hippocampus.khaki3)) {
print("No significant pathways")
} else {genes.hippocampus.khaki3 <- genes.hippocampus.khaki3$result
DT.table.jaccard(genes.hippocampus.khaki3[c(11,4:6,3)])
}## [1] "No significant pathways"genes.hypothalamus.midnightblue <- genes.jaccard.pathways(Matched, "Hypothalamus_midnightblue")if(is.null(genes.hypothalamus.midnightblue)) {
print("No significant pathways")
} else {genes.hypothalamus.midnightblue <- genes.hypothalamus.midnightblue$result
DT.table.jaccard(genes.hypothalamus.midnightblue[c(11,4:6,3)])
}genes.hypothalamus.bisque4 <- genes.jaccard.pathways(Matched, "Hypothalamus_bisque4")if(is.null(genes.hypothalamus.bisque4)) {
print("No significant pathways")
} else {genes.hypothalamus.bisque4 <- genes.hypothalamus.bisque4$result
DT.table.jaccard(genes.hypothalamus.bisque4[c(11,4:6,3)])
}genes.kidney.lightyellow <- genes.jaccard.pathways(Matched, "Kidney_lightyellow")if(is.null(genes.kidney.lightyellow)) {
print("No significant pathways")
} else {genes.kidney.lightyellow <- genes.kidney.lightyellow$result
DT.table.jaccard(genes.kidney.lightyellow[c(11,4:6,3)])
}genes.kidney.purple <- genes.jaccard.pathways(Matched, "Kidney_purple")if(is.null(genes.kidney.purple)) {
print("No significant pathways")
} else {genes.kidney.purple <- genes.kidney.purple$result
DT.table.jaccard(genes.kidney.purple[c(11,4:6,3)])
}## [1] "No significant pathways"genes.kidney.lightcyan <- genes.jaccard.pathways(Matched, "Kidney_lightcyan")if(is.null(genes.kidney.lightcyan)) {
print("No significant pathways")
} else {genes.kidney.lightcyan <- genes.kidney.lightcyan$result
DT.table.jaccard(genes.kidney.lightcyan[c(11,4:6,3)])
}## [1] "No significant pathways"Server won’t run this module currently
#genes.kidney.blue <- genes.jaccard.pathways(Matched, "Kidney_blue")# if(is.null(genes.kidney.blue)) {
# print("No significant pathways")
# } else {genes.kidney.blue <- genes.kidney.blue$result
# DT.table.jaccard(genes.kidney.blue[c(11,4:6,3)])
#
# }genes.kidney.pink <- genes.jaccard.pathways(Matched, "Kidney_pink")if(is.null(genes.kidney.pink)) {
print("No significant pathways")
} else {genes.kidney.pink <- genes.kidney.pink$result
DT.table.jaccard(genes.kidney.pink[c(11,4:6,3)])
}genes.liver.darkturquoise <- genes.jaccard.pathways(Matched, "Liver_darkturquoise")if(is.null(genes.liver.darkturquoise)) {
print("No significant pathways")
} else {genes.liver.darkturquoise <- genes.liver.darkturquoise$result
DT.table.jaccard(genes.liver.darkturquoise[c(11,4:6,3)])
}genes.liver.darkolivegreen <- genes.jaccard.pathways(Matched, "Liver_darkolivegreen")if(is.null(genes.liver.darkolivegreen)) {
print("No significant pathways")
} else {genes.liver.darkolivegreen <- genes.liver.darkolivegreen$result
DT.table.jaccard(genes.liver.darkolivegreen[c(11,4:6,3)])
}genes.liver.skyblue3 <- genes.jaccard.pathways(Matched, "Liver_skyblue3")if(is.null(genes.liver.skyblue3)) {
print("No significant pathways")
} else {genes.liver.skyblue3 <- genes.liver.skyblue3$result
DT.table.jaccard(genes.liver.skyblue3[c(11,4:6,3)])
}genes.prefrontal.limegreen <- genes.jaccard.pathways(Matched, "Prefrontal Cortex_limegreen")if(is.null(genes.prefrontal.limegreen)) {
print("No significant pathways")
} else {genes.prefrontal.limegreen <- genes.prefrontal.limegreen$result
DT.table.jaccard(genes.prefrontal.limegreen[c(11,4:6,3)])
}## [1] "No significant pathways"genes.prefrontal.rosybrown2 <- genes.jaccard.pathways(Matched, "Prefrontal Cortex_rosybrown2")if(is.null(genes.prefrontal.rosybrown2)) {
print("No significant pathways")
} else {genes.prefrontal.rosybrown2 <- genes.prefrontal.rosybrown2$result
DT.table.jaccard(genes.prefrontal.rosybrown2[c(11,4:6,3)])
}genes.prefrontal.lavenderblush2 <- genes.jaccard.pathways(Matched, "Prefrontal Cortex_lavenderblush2")if(is.null(genes.prefrontal.lavenderblush2)) {
print("No significant pathways")
} else {genes.prefrontal.lavenderblush2 <- genes.prefrontal.lavenderblush2$result
DT.table.jaccard(genes.prefrontal.lavenderblush2[c(11,4:6,3)])
}genes.prefrontal.antiquewhite <- genes.jaccard.pathways(Matched, "Prefrontal Cortex_antiquewhite")if(is.null(genes.prefrontal.antiquewhite)) {
print("No significant pathways")
} else {genes.prefrontal.antiquewhite <- genes.prefrontal.antiquewhite$result
DT.table.jaccard(genes.prefrontal.antiquewhite[c(11,4:6,3)])
}## [1] "No significant pathways"genes.prefrontal.pink <- genes.jaccard.pathways(Matched, "Prefrontal Cortex_pink")if(is.null(genes.prefrontal.pink)) {
print("No significant pathways")
} else {genes.prefrontal.pink <- genes.prefrontal.pink$result
DT.table.jaccard(genes.prefrontal.pink[c(11,4:6,3)])
}genes.prefrontal.goldenrod3 <- genes.jaccard.pathways(Matched, "Prefrontal Cortex_goldenrod3")if(is.null(genes.prefrontal.goldenrod3)) {
print("No significant pathways")
} else {genes.prefrontal.goldenrod3 <- genes.prefrontal.goldenrod3$result
DT.table.jaccard(genes.prefrontal.goldenrod3[c(11,4:6,3)])
}## [1] "No significant pathways"genes.prefrontal.aquamarine <- genes.jaccard.pathways(Matched, "Prefrontal Cortex_aquamarine")if(is.null(genes.prefrontal.aquamarine)) {
print("No significant pathways")
} else {genes.prefrontal.aquamarine <- genes.prefrontal.aquamarine$result
DT.table.jaccard(genes.prefrontal.aquamarine[c(11,4:6,3)])
}genes.skeletal.grey <- genes.jaccard.pathways(Matched, "Skeletal Muscle_grey")if(is.null(genes.skeletal.grey)) {
print("No significant pathways")
} else {genes.skeletal.grey <- genes.skeletal.grey$result
DT.table.jaccard(genes.skeletal.grey[c(11,4:6,3)])
}genes.intestine.green4 <- genes.jaccard.pathways(Matched, "Small Intestine_green4")if(is.null(genes.intestine.green4)) {
print("No significant pathways")
} else {genes.intestine.green4 <- genes.intestine.green4$result
DT.table.jaccard(genes.intestine.green4[c(11,4:6,3)])
}genes.intestine.blue2 <- genes.jaccard.pathways(Matched, "Small Intestine_blue2")if(is.null(genes.intestine.blue2)) {
print("No significant pathways")
} else {genes.intestine.blue2 <- genes.intestine.blue2$result
DT.table.jaccard(genes.intestine.blue2[c(11,4:6,3)])
}genes.intestine.cornsilk <- genes.jaccard.pathways(Matched, "Small Intestine_cornsilk")if(is.null(genes.intestine.cornsilk)) {
print("No significant pathways")
} else {genes.intestine.cornsilk <- genes.intestine.cornsilk$result
DT.table.jaccard(genes.intestine.cornsilk[c(11,4:6,3)])
}genes.intestine.magenta2 <- genes.jaccard.pathways(Matched, "Small Intestine_magenta2")if(is.null(genes.intestine.magenta2)) {
print("No significant pathways")
} else {genes.intestine.magenta2 <- genes.intestine.magenta2$result
DT.table.jaccard(genes.intestine.magenta2[c(11,4:6,3)])
}## [1] "No significant pathways"genes.intestine.darkgoldenrod4 <- genes.jaccard.pathways(Matched, "Small Intestine_darkgoldenrod4")if(is.null(genes.intestine.darkgoldenrod4)) {
print("No significant pathways")
} else {genes.intestine.darkgoldenrod4 <- genes.intestine.darkgoldenrod4$result
DT.table.jaccard(genes.intestine.darkgoldenrod4[c(11,4:6,3)])
}## [1] "No significant pathways"genes.spleen.tan4 <- genes.jaccard.pathways(Matched, "Spleen_tan4")if(is.null(genes.spleen.tan4)) {
print("No significant pathways")
} else {genes.spleen.tan4 <- genes.spleen.tan4$result
DT.table.jaccard(genes.spleen.tan4[c(11,4:6,3)])
}genes.spleen.mediumpurple1 <- genes.jaccard.pathways(Matched, "Spleen_mediumpurple1")if(is.null(genes.spleen.mediumpurple1)) {
print("No significant pathways")
} else {genes.spleen.mediumpurple1 <- genes.spleen.mediumpurple1$result
DT.table.jaccard(genes.spleen.mediumpurple1[c(11,4:6,3)])
}genes.spleen.palevioletred3 <- genes.jaccard.pathways(Matched, "Spleen_palevioletred3")if(is.null(genes.spleen.palevioletred3)) {
print("No significant pathways")
} else {genes.spleen.palevioletred3 <- genes.spleen.palevioletred3$result
DT.table.jaccard(genes.spleen.palevioletred3[c(11,4:6,3)])
}Analysis performed by Ann Wells
The Carter Lab The Jackson Laboratory 2023
ann.wells@jax.org