Module Sample Contribution
Ann Wells
April 23, 2023
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()
modules <- read.csv(here("Data","log.tdata.FPKM.sample.info.subset.WGCNA.module.membership.csv"), header=T)
eigens <- read.csv(here("Data","log.tdata.FPKM.sample.info.subset.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)lightyellow Module
turquoise Module
darkgreen Module
darkolivegreen Module
black Module
midnightblue Module
pink Module
skyblue Module
lightcyan Module
darkorange2 Module
mediumpurple3 Module
royalblue Module
lightsteelblue1 Module
violet Module
skyblue3 Module
orangered4 Module
lightcyan1 Module
ivory Module
floralwhite Module
grey Module
Module Sample Contribution Dot plot
dot.plot(eigens)lightyellow Module
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turquoise Module
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darkgreen Module
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darkolivegreen Module
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black Module
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midnightblue Module
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pink Module
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skyblue Module
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lightcyan Module
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darkorange2 Module
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mediumpurple3 Module
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royalblue Module
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lightsteelblue1 Module
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violet Module
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skyblue3 Module
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orangered4 Module
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lightcyan1 Module
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ivory Module
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floralwhite Module
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grey Module
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Analysis performed by Ann Wells
The Carter Lab The Jackson Laboratory 2023
ann.wells@jax.org