Chapter 1 Overview

This bookdown tutorial demonstrates differential expression analysis on GSE233947, which provides a FeatureCounts raw-count matrix as a GEO supplementary file (GSE233947_FeatureCounts_V31genes_RawCounts_ENSG.tsv.gz).

We implement three DE workflows in clearly separated chapters:

  • limma-voom (Chapter 4)
  • edgeR (quasi-likelihood) (Chapter 5)
  • DESeq2 (Chapter 6)

In addition, it also demonstrates the analysis of differential expression analysis on a messy dataset GSE240829, which provides multiple files on GEO, two are TPM and one is labelled as salmon feature counts so for argument’s sake I am going to assume that it is salmon estimated counts (as opposed to TPM, like the other files.).

  • limma-voom (Chapter @ref(limma-voom_dataset2))
  • edgeR (quasi-likelihood) –> well we try quasi-likelihood (Chapter @ref(edger_dataset2))
  • DESeq2 (Chapter @ref(deseq2_dataset2))

1.1 Packages

# Install once if needed:
if(!require(tidyverse)){
  install.packages(c("tidyverse"))
}
library(GEOquery)
library(edgeR)
library(limma)
library(tidyverse)
library(ComplexHeatmap)
library(RColorBrewer)
library(circlize)

1.2 Reproducibility

  • Run this project in RStudio.
  • Click Build → Build Book (or run bookdown::render_book("index.Rmd")).