HTSanalyzeR (version 2.24.0)

analyze: Gene Set Collection Analysis or NetWork Analysis

Description

This is a generic function.

When implemented as the S4 method for objects of class GSCA, this function invokes function analyzeGeneSetCollections to do hypergeometic tests and GSEA.

When implemented on an object of class NWA, it calls function networkAnalysis to do subnetwork identification.

To use this function for objects of class GSCA:

analyze(object, para = list(pValueCutoff = 0.05, pAdjustMethod = "BH", nPermutations = 1000, minGeneSetSize = 15, exponent = 1), verbose = TRUE, doGSCA=TRUE, doGSEA=TRUE)

To use this function for objects of class NWA:

analyze(object, fdr=0.001, species, verbose=TRUE)

Usage

analyze(object, ...)

Arguments

object

an object. When this function is implemented as the S4 method of class 'GSCA' or 'NWA', this argument is an object of class 'GSCA' or 'NWA'.

...

other arguments depending on class (see below for the arguments supported by the method of class 'GSCA' or 'NWA')

Value

In the end, this function will return an updated object of class GSCA or NWA.

Details

For objects of class GSCA:

The function will store the results from function analyzeGeneSetCollections in slot result, and update information about these results to slot summary of class GSCA.

See function analyzeGeneSetCollections for the detailed information about the returned results.

For objects of class NWA:

The function will store the subnetwork module identified by BioNet (if species is given, labels of nodes will also be mapped from Entrez IDs to gene symbols), and update information about these results to slot summary of class NWA.

See function networkAnalysis for the detailed information about the returned results.

References

Beisser D, Klau GW, Dandekar T, Muller T, Dittrich MT. BioNet: an R-Package for the functional analysis of biological networks. Bioinformatics. 2010 Apr 15;26(8):1129-30.

Dittrich MT, Klau GW, Rosenwald A., Dandekar T and Muller T. Identifying functional modules in protein-protein interaction networks: an integrated exact approach. Bioinformatics 2008 24(13): i223-i231.

See Also

analyzeGeneSetCollections, networkAnalysis

Examples

## Not run: 
# library(org.Dm.eg.db)
# library(KEGG.db)
# ##load data for enrichment analyses
# data("KcViab_Data4Enrich")
# ##select hits
# hits <- names(KcViab_Data4Enrich)[which(abs(KcViab_Data4Enrich) > 2)]
# ##set up a list of gene set collections
# PW_KEGG <- KeggGeneSets(species = "Dm")
# gscList <- list(PW_KEGG = PW_KEGG)
# ##create an object of class 'GSCA'
# gsca <- new("GSCA", listOfGeneSetCollections=gscList,
# geneList = KcViab_Data4Enrich, hits = hits)
# ##print gsca
# gsca
# ##do preprocessing (KcViab_Data4Enrich has already been preprocessed)
# gsca <- preprocess(gsca, species="Dm", initialIDs = "Entrez.gene", 
# keepMultipleMappings = TRUE, duplicateRemoverMethod = "max", 
# orderAbsValue = FALSE)
# ##print gsca again
# gsca
# ##do hypergeometric tests and GSEA
# gsca <- analyze(gsca, para = list(pValueCutoff = 0.05, pAdjustMethod 
# = "BH", nPermutations = 1000, minGeneSetSize = 100,exponent = 1), doGSOA=TRUE, 
# doGSEA=TRUE)
# ##updated object
# gsca
# summarize(gsca)
# ## End(Not run)