dgeWithEdgeR: Perform differential gene expression analysis with edgeR

In bedapub/ribiosNGS: Utilities for next-generation sequencing data analysis in ribios

Perform differential gene expression analysis with edgeR

Description

Perform differential gene expression analysis with edgeR

Usage

dgeWithEdgeR(edgeObj)

Arguments

edgeObj

An object of EdgeObject The function performs end-to-end differential gene expression (DGE) analysis with common best practice using edgeR

Value

An EdgeResult object

Examples

exMat <- matrix(rpois(120, 10), nrow=20, ncol=6)
exGroups <- gl(2,3, labels=c("Group1", "Group2"))
exDesign <- model.matrix(~0+exGroups)
colnames(exDesign) <- levels(exGroups)
exContrast <- matrix(c(-1,1), ncol=1, dimnames=list(c("Group1", "Group2"), c("Group2.vs.Group1")))
exDescon <- DesignContrast(exDesign, exContrast, groups=exGroups)
exFdata <- data.frame(Identifier=sprintf("Gene%d", 1:nrow(exMat)))
exPdata <- data.frame(Name=sprintf("Sample%d", 1:ncol(exMat)),
                     Group=exGroups)
exObj <- EdgeObject(exMat, exDescon, 
                     fData=exFdata, pData=exPdata)
exDgeRes <- dgeWithEdgeR(exObj)
dgeTable(exDgeRes)

bedapub/ribiosNGS documentation built on Feb. 10, 2025, 12:34 a.m.