TCGAanalyze_EA: Enrichment analysis of a gene-set with GO [BP,MF,CC] and pathways.

Description

The rational behind a enrichment analysis ( gene-set, pathway etc) is to compute statistics of whether the overlap between the focus list (signature) and the gene-set is significant. ie the confidence that overlap between the list is not due to chance. The Gene Ontology project describes genes (gene products) using terms from three structured vocabularies: biological process, cellular component and molecular function. The Gene Ontology Enrichment component, also referred to as the GO Terms" component, allows the genes in any such "changed-gene" list to be characterized using the Gene Ontology terms annotated to them. It asks, whether for any particular GO term, the fraction of genes assigned to it in the "changed-gene" list is higher than expected by chance (is over-represented), relative to the fraction of genes assigned to that term in the reference set. In statistical terms it peform the analysis tests the null hypothesis that, for any particular ontology term, there is no diffeerence in the proportion of genes annotated to it in the reference list and the proportion annotated to it in the test list. We adopted a Fisher Exact Test to perform the EA.

Usage

TCGAanalyze_EA(GeneName, RegulonList, TableEnrichment, EAGenes, GOtype, FDRThresh = 0.01)

Arguments

GeneName

is the name of gene signatures list

RegulonList

is a gene signature (lisf of genes) in which perform EA.

TableEnrichment

is a table related to annotations of gene symbols such as GO[BP,MF,CC] and Pathways. It was created from DAVID gene ontology on-line.

EAGenes

is a table with informations about genes such as ID, Gene, Description, Location and Family.

GOtype

is type of gene ontology Biological process (BP), Molecular Function (MF), Cellular componet (CC)

FDRThresh

pvalue corrected (FDR) as threshold to selected significant BP, MF,CC, or pathways. (default FDR < 0.01)

Value

Table with enriched GO or pathways by selected gene signature.

Examples

Run this code

## Not run: 
# EAGenes <- get("EAGenes")
# RegulonList <- rownames(dataDEGsFiltLevel)
# ResBP <- TCGAanalyze_EA(GeneName="DEA genes Normal Vs Tumor",
#                            RegulonList,DAVID_BP_matrix,
#                            EAGenes,GOtype = "DavidBP")
# ## End(Not run)

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