3 Basic Usage

This chapter introduces practical workflows for analyzing RNA-seq count data with normpatch. The examples follow the main steps in a typical analysis: download a count matrix, prepare the experimental design, estimate normalization factors, and perform DEG analysis.

To reproduce the examples, install the required R packages. ExpressionAtlas is used to download datasets from the EBI Expression Atlas, while edgeR and DESeq2 are used for DEG analysis after normalization.

BiocManager::install(c("ExpressionAtlas", "edgeR", "DESeq2"))

Then load the packages used by the examples.

library(ExpressionAtlas)
library(edgeR)
library(DESeq2)
library(normpatch)
library(ggplot2)

As with edgeR and DESeq2, normpatch requires raw, unnormalized integer counts as input. Do not use transcripts per million (TPM), fragments per kilobase of transcript per million mapped reads (FPKM), counts per million (CPM), normalized counts, or log transformed expression values.