estimate_go_overrep: Estimate effect size of GO over-representation

In CambridgeCentreForProteomics/camprotR: Processing, analysing and visualising CCP proteomics data

Estimate effect size of GO over-representation

Description

This is a crude function to estimate the effect size of GO over-representation i.e. we know a term is over-represented, but we want to estimate the effect size/how over-represented it is. This function should be run after get_enriched_go.

Usage

estimate_go_overrep(obj, pwf, gene2cat)

Arguments

obj	data.frame containing goseq results as generated by get_enriched_go or goseq.
pwf	data.frame as used in get_enriched_go or goseq.
gene2cat	data.frame as used in get_enriched_go or goseq.

Value

Returns obj with an extra column added called adj_overrep. This column is calculated for each GO term by:

numDEInCat / numInCat / (avgTermWeight / avgNonTermWeight) / (totalDEFeatures / totalFeatures)

where:

• numDEInCat is the number of differentially expressed genes (aka. proteins) assigned to that GO term.

• numInCat is the total number of genes (aka. proteins) annotated to that GO term.

• avgTermWeight is the average pwf$pwf value for all the differentially expressed genes that were assigned to that GO term.

• avgNonTermWeight is the average pwf$pwf for all the other genes supplied in pwf.

• totalDEFeatures is the total number of differentially expressed genes indicated in pwf.

• totalFeatures is the total number of genes indicated in pwf, i.e. the number of rows.

CambridgeCentreForProteomics/camprotR documentation built on Jan. 27, 2023, 8:36 p.m.