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 (add dosage) 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.SM.SI.spleen <- log.tdata.FPKM.sample.info.subset %>% rownames_to_column() %>% filter(Tissue %in% c("Skeletal Muscle", "Spleen", "Small Intestine")) %>% column_to_rownames()

modules <- read.csv(here("Data","SM.SI.spleen","log.tdata.FPKM.sample.info.subset.SM.SI.spleen.WGCNA.module.membership.csv"), header=T)
eigens <- read.csv(here("Data","SM.SI.spleen","log.tdata.FPKM.sample.info.subset.SM.SI.spleen.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.SM.SI.spleen)

turquoise Module

blue Module

brown Module

green Module

Module Sample Contribution Dot plot

dot.plot(eigens)

turquoise Module

Time

Treatment

Tissue

Time_by_Treatment

Time_by_Tissue

Treatment_by_Tissue

Time_by_Treatment_by_Tissue

blue Module

Time

Treatment

Tissue

Time_by_Treatment

Time_by_Tissue

Treatment_by_Tissue

Time_by_Treatment_by_Tissue

brown Module

Time

Treatment

Tissue

Time_by_Treatment

Time_by_Tissue

Treatment_by_Tissue

Time_by_Treatment_by_Tissue

green Module

Time

Treatment

Tissue

Time_by_Treatment

Time_by_Tissue

Treatment_by_Tissue

Time_by_Treatment_by_Tissue

Analysis performed by Ann Wells

The Carter Lab The Jackson Laboratory 2023

ann.wells@jax.org