DESeq2Fit: Analysis of LPS RFI RNA-seq data Using DESeq2

In ntyet/rmRNAseq: RNA-Seq Analysis for Repeated-Measures Data

Analysis of LPS RFI RNA-seq data Using DESeq2

Description

This function analyzes the LPS RFI RNA-seq data and simulated datasets using DESeq, the Quasi-likelihood F-test in DESeq2 package.

Usage

DESeq2Fit(counts, design, Effect)

Arguments

counts	a matrix of count data.
design	a design matrix.
Effect	the effect used to simulate data, either line2, or time. This effect is considered as the main factor of interest where the status of DE and EE genes was specified. @param covset a data frame contain covariate set.

Value

a list of 4 components

fit	output of DESeq function.
pv	a vector of p-values of the test for significant of Effect.
qv	a vector of q-values corresponding to the pv above.

Examples

data(dat)
data(design)
counts <- dat[1:100,]
design <- design
Effect <- "line2"
DESeq2Fitout <- rmRNAseq:::DESeq2Fit(counts, design, Effect)
names(DESeq2Fitout)

ntyet/rmRNAseq documentation built on July 7, 2023, 11:10 a.m.