BI_edgeR1: Differencially expression analysis via edgeR package

In shijianasdf/BasicBioinformaticsAnalysisFromZhongShan: Launch Usual Clinical tool for Kind Yield

Description

edgeR1 help do rawcounts-based differencially expression analysis via edgeR package.

Usage

edgeRList <- edgeR1(counts,
                    design,
                    contrast.col,
                    contrast.level = c("Treat","Control"),
                    contrast.control = "Control",
                    cutoff.lFC = 1,
                    cutoff.padj = 0.1,
                    show.report = F,
                    save.file = T,
                    names = "love")

Arguments

counts	raw counts
design	design object
contrast.col	contrast colname in the design object
contrast.level	the order should be treat then control
contrast.control	the control of the contrast level
cutoff.lFC	the cut-off of log fold change
cutoff.padj	the cut-off of FDR
save.report	whether to show quality control report
save.file	whether to save edgeRList
names	part name of saved file

Value

edgeRList object that containing significant genes,significant information and edgeR fit object

Author(s)

Weibin Huang<[e-mail]>

See Also

edgeR::calcNormFactors edgeR::estimateDisp edgeR::glmQLFit edgeR::glmQLFTest

Examples

## This is a simulative process and NOT RUN
counts = data.counts;rm(data.counts)
design = design.train2
contrast.col = "N.status"
contrast.level = c("Np","N0")
contrast.contol = "N0"
count.filter=10
cutoff.lFC = 1
cutoff.padj = 0.1
save.file = T
names = "love"

## Quick Start
edgeRList <- edgeR1(counts,
                    design,
                    contrast.col,
                    contrast.level,
                    contrast.control,
                    names = "love")

## Complex Setting
edgeRList <- edgeR1(counts,
                    design,
                    contrast.col,
                    contrast.level = c("Treat","Control"),
                     contrast.level = "Control",
                    cutoff.lFC = 1,
                    cutoff.padj = 0.1,
                    save.file = T,
                    names = "love")

shijianasdf/BasicBioinformaticsAnalysisFromZhongShan documentation built on Jan. 3, 2020, 10:08 p.m.