Introduction and Data files

R Markdown

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 determine how samples are contributing to each module.

needed.packages <- c("tidyverse", "here", "functional", "gplots", "dplyr", "GeneOverlap", "R.utils", "reshape2","magrittr","data.table", "RColorBrewer","preprocessCore", "ARTool","emmeans", "phia", "gProfileR","pheatmap")
for(i in 1:length(needed.packages)){library(needed.packages[i], character.only = TRUE)}

source(here("source_files","WGCNA_source.R"))
source(here("source_files","plot_theme.R"))
tdata.FPKM.sample.info <- readRDS(here("Data","20190406_RNAseq_B6_4wk_2DG_counts_phenotypes.RData"))

tdata.FPKM <- readRDS(here("Data","20190406_RNAseq_B6_4wk_2DG_counts_numeric.RData"))

log.tdata.FPKM <- log(tdata.FPKM + 1)
log.tdata.FPKM <- as.data.frame(log.tdata.FPKM)

log.tdata.FPKM.sample.info <- cbind(log.tdata.FPKM, tdata.FPKM.sample.info[,27238:27240])

log.tdata.FPKM.sample.info <- log.tdata.FPKM.sample.info %>% rownames_to_column() %>% filter(rowname != "A113") %>% column_to_rownames()

log.tdata.FPKM.subset <- log.tdata.FPKM[,colMeans(log.tdata.FPKM != 0) > 0.5] 

log.tdata.FPKM.sample.info.subset <- cbind(log.tdata.FPKM.subset,tdata.FPKM.sample.info[,27238:27240])
log.tdata.FPKM.sample.info.subset <- log.tdata.FPKM.sample.info.subset %>% rownames_to_column() %>% filter(rowname != "A113") %>% column_to_rownames()

log.tdata.FPKM.sample.info.subset.prefrontal.cortex <- log.tdata.FPKM.sample.info.subset %>% rownames_to_column() %>% filter(Tissue == "Pre-frontal Cortex") %>% column_to_rownames()

modules <- read.csv(here("Data","Prefrontal Cortex","log.tdata.FPKM.sample.info.subset.prefrontal.cortex.WGCNA.module.membership.csv"), header=T)
eigens <- read.csv(here("Data","Prefrontal Cortex","log.tdata.FPKM.sample.info.subset.prefrontal.cortex.WGCNA.module.eigens.csv"), header=T)

Module Sample Contribution

The heatmap shows the expression level of each gene in the module across all samples present in this subsetted dataset. The bar plot shows the relative eigen value summarizing gene expression for each sample present in this subsetted dataset.

eigen.expression(eigens,log.tdata.FPKM.sample.info.subset.prefrontal.cortex)

blanchedalmond Module

chocolate4 Module

black Module

lightgoldenrod3 Module

darkolivegreen2 Module

aquamarine Module

bisque2 Module

darkolivegreen4 Module

grey Module

blueviolet Module

darkturquoise Module

khaki3 Module

dodgerblue4 Module

cornsilk2 Module

darkseagreen4 Module

lightpink1 Module

antiquewhite Module

pink Module

salmon Module

lavenderblush2 Module

plum Module

goldenrod3 Module

chocolate2 Module

blue4 Module

mistyrose Module

cornsilk Module

lightskyblue2 Module

burlywood Module

oldlace Module

lightblue Module

limegreen Module

hotpink3 Module

lightskyblue Module

mediumorchid1 Module

rosybrown2 Module

Module Sample Contribution Dot plot

dot.plot(eigens)

blanchedalmond Module

Time

Treatment

Time_by_Treatment

chocolate4 Module

Time

Treatment

Time_by_Treatment

black Module

Time

Treatment

Time_by_Treatment

lightgoldenrod3 Module

Time

Treatment

Time_by_Treatment

darkolivegreen2 Module

Time

Treatment

Time_by_Treatment

aquamarine Module

Time

Treatment

Time_by_Treatment

bisque2 Module

Time

Treatment

Time_by_Treatment

darkolivegreen4 Module

Time

Treatment

Time_by_Treatment

grey Module

Time

Treatment

Time_by_Treatment

blueviolet Module

Time

Treatment

Time_by_Treatment

darkturquoise Module

Time

Treatment

Time_by_Treatment

khaki3 Module

Time

Treatment

Time_by_Treatment

dodgerblue4 Module

Time

Treatment

Time_by_Treatment

cornsilk2 Module

Time

Treatment

Time_by_Treatment

darkseagreen4 Module

Time

Treatment

Time_by_Treatment

lightpink1 Module

Time

Treatment

Time_by_Treatment

antiquewhite Module

Time

Treatment

Time_by_Treatment

pink Module

Time

Treatment

Time_by_Treatment

salmon Module

Time

Treatment

Time_by_Treatment

lavenderblush2 Module

Time

Treatment

Time_by_Treatment

plum Module

Time

Treatment

Time_by_Treatment

goldenrod3 Module

Time

Treatment

Time_by_Treatment

chocolate2 Module

Time

Treatment

Time_by_Treatment

blue4 Module

Time

Treatment

Time_by_Treatment

mistyrose Module

Time

Treatment

Time_by_Treatment

cornsilk Module

Time

Treatment

Time_by_Treatment

lightskyblue2 Module

Time

Treatment

Time_by_Treatment

burlywood Module

Time

Treatment

Time_by_Treatment

oldlace Module

Time

Treatment

Time_by_Treatment

lightblue Module

Time

Treatment

Time_by_Treatment

limegreen Module

Time

Treatment

Time_by_Treatment

hotpink3 Module

Time

Treatment

Time_by_Treatment

lightskyblue Module

Time

Treatment

Time_by_Treatment

mediumorchid1 Module

Time

Treatment

Time_by_Treatment

rosybrown2 Module

Time

Treatment

Time_by_Treatment


Analysis performed by Ann Wells

The Carter Lab The Jackson Laboratory 2023

ann.wells@jax.org