ora: Traditional Overrepresentation Analysis.

In sigora: Signature Overrepresentation Analysis

Traditional Overrepresentation Analysis.

Description

Traditional Overrepresentation Analysis by hypergeometric test: pathways are treated as collections of individual genes and all genes are treated as equally informative. This function is provided for comparison of the results of traditional methods to Sigora.

Usage

ora(geneList, GPSrepo, idmap = load_data("idmap"))

Arguments

geneList	A vector containing the list of genes of interest (e.g. differentially expressed genes). Following Identifier types are supported: Gene Symbols, ENTREZ-IDs or ENSEMBL-IDs.
GPSrepo	A GPS-repository (either one of the provided precomputed GPS repositories) or one created by makeGPS.
idmap	A dataframe for converting between different gene-identifier types (e.g. ENSEMBL, ENTREZ and HGNC-Symbols of genes). Most users do not need to set this argument, as there is a built-in conversion table.

Details

The primary purpose of makeGPS is to create a GPS repository. It does, however, retain the original "single gene"-"pathway" associations for the purpose of followup analyses, such as comparison of sigora-results to traditional methods. ora is an implementation of the traditional (individual gene) Overrepresentation Analysis.

Value

A dataframe with individual gene ORA results.

See Also

sigora-package

Examples

data(kegM)
## select 50 genes from 3 mouse pathways
set.seed(seed=345)
a1<-genesFromRandomPathways(kegM,3,50)
## originally selected pathways:
a1[["selectedPathways"]]
## compare to traditional methods results:
oraRes <- ora(a1[["genes"]],kegM)
dim(oraRes)
oraRes

sigora documentation built on March 18, 2022, 8:05 p.m.