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SeqGSEA (version 1.8.1)

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

Description

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.

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Version

Version

1.8.1

License

GPL (>= 3)

Maintainer

Xi Wang

Last Published

February 15th, 2017

Functions in SeqGSEA (1.8.1)

convertEnsembl2Symbol

Convert ensembl gene IDs to gene symbols

Accessors for the 'counts' slot of a ReadCountSet object.

Calculate running enrichment scores of gene sets

Permutation for p-values in differential expression analysis

Calculate enrichment scores for gene sets in the permutation data sets

Pre-calculated DE/DS scores

DENBStatPermut4GSEA

Calculate NB-statistics quantifying DE for each gene in the permutation data sets

convertSymbol2Ensembl

Convert gene symbols to ensembl gene IDs

Calculate NB-statistics quantifying differential expression for each gene

Perform negative binomial exact test for differential expression

Accessor to the geneID slot of ReadCountSet objects

Compute NB-statistics quantifying differential splicing on the permutation data set.

Permutation for p-values in differential splicing analysis

Calculate NB-statistics quantifying differential splicing for individual exons

Get the gene list in a SeqGeneSet object

Calculate NB-statistics quantifying differential splicing for each gene

DSresultExonTable

Form a table for DS analysis results at the Exon level

DSresultGeneTable

Form a table for DS analysis results at the gene level

Accessor to the exonID slot of ReadCountSet objects

exonTestability

Check exon testability

SeqGeneSet object example

GSEAresultTable

Form a table for GSEA results

Calculate read counts of genes from a ReadCountSet object

Generate permutation matrix

Get the names of gene set in a SeqGeneSet object

Get the descriptions of gene sets in a SeqGeneSet object

Get the numbers of genes in each gene set in a SeqGeneSet object

geneTestability

Check gene testability

genePermuteScore

Calculate gene scores on permutation data sets

Calculate gene scores by integrating DE and DS scores

Plot showing SeqGeneSet's p-values/FDRs vs. NESs

loadExonCountData

Load Exon Count Data

Load gene sets from files

Plot gene set details

Write DE/DS scores and gene scores

ReadCountSet-class

Class "ReadCountSet"

Extract top significant gene sets

Run DESeq for differential expression analysis

Extract top differentially spliced genes

Extract top differentially spliced exons

SeqGSEA-package

SeqGSEA: a Bioconductor package for gene set enrichment analysis of RNA-Seq data

SeqGeneSet-class

Class "SeqGeneSet"

Get the labels of samples in a ReadCountSet object

GSEnrichAnalyze

Main function of gene set enrichment analysis

Number of gene sets in a SeqGeneSet object

Calculate significance of ESs

Normalize enrichment scores

Get normalization factors for normalization DE or DS scores

Integration of differential expression and differential splice scores with a rank-based strategy

ReadCountSet object example

newReadCountSet

Generate a new ReadCountSet object

writeSigGeneSet

Write gene set supporting information

Initialize a new SeqGeneSet object

An all-in function that allows end users to apply SeqGSEA to their data with one step.

Plot the distribution of enrichment scores

Plot gene (DE/DS) scores

scoreNormalization

Normalization of DE/DS scores

Get a new ReadCountSet with specified gene IDs.

Extract top differentially expressed genes.