runDESeq

a matrix containing read counts for each gene, can be the output of <code><a rd-options="" href="/link/getGeneCount?package=SeqGSEA&version=1.12.0" data-mini-rdoc="SeqGSEA::getGeneCount">getGeneCount</a></code>.

geneCounts

label


This function provides a wrapper to run DESeq for differential expression analysis. It includes two steps, 
<code>DESeq::estimateSizeFactors</code> and <code>DESeq::estimateDispersions</code>. 


The package generally provides methods for gene set
enrichment analysis of high-throughput RNA-Seq data by
integrating differential expression and splicing. It uses
negative binomial distribution to model read count data, which
accounts for sequencing biases and biological variation. Based
on permutation tests, statistical significance can also be
achieved regarding each gene's differential expression and
splicing, respectively.

Xi Wang

SeqGSEA

Gene Set Enrichment Analysis (GSEA) of RNA-Seq Data: integrating
differential expression and splicing

runDESeq function

a matrix containing read counts for each gene, can be the output of <code><a href="getGeneCount" rd-options="">getGeneCount</a></code>.

This function provides a wrapper to run DESeq for differential expression analysis. It includes two steps, 
<code>DESeq::estimateSizeFactors</code> and <code>DESeq::estimateDispersions</code>.

runDESeq: Run DESeq for differential expression analysis

Description

Usage

Arguments

Value

References

See Also

Examples