enrichedAnnotations: Tests the NULL Hypothesis for each gene (function) annotation...

In asishallab/GeneFamilies: Analyses different properties of gene families

Tests the NULL Hypothesis for each gene (function) annotation in annos.2.test that its annotation-frequency in the case.genes is explicable with the background distribution observed in universe.annos. The default alternative hypothesis is that the actual case frequency is 'greater'.

Description

Tests the NULL Hypothesis for each gene (function) annotation in annos.2.test that its annotation-frequency in the case.genes is explicable with the background distribution observed in universe.annos. The default alternative hypothesis is that the actual case frequency is 'greater'.

Usage

enrichedAnnotations(case.genes, universe.annos = all.ipr,
  univ.gene.col = 1, univ.anno.col = 2,
  annos.2.test = unique(universe.annos[which(universe.annos[,
  univ.gene.col] %in% case.genes), univ.anno.col]),
  alt.hypothesis = "greater", p.adjust.method = "BY")

Arguments

case.genes	A character vector of gene identifiers defining the gene group of interest for which to infer enriched annotations.
universe.annos	A data.frame with at least two columns: 1. of gene identifiers and another of (function) annotations. Default is this package's data all.ipr.
univ.gene.col	The column of universe.annos in which to lookup gene identifier. Default is 1.
univ.anno.col	The column of universe.annos in which to lookup annotations. Default is 2.
annos.2.test	The annotations for which to test enrichment. Default is all annotations found for the case.genes.
alt.hypothesis	The alternative hypotheses to test. Default is that the case frequencies are significantly greater than the one observed in the 'universe'.
p.adjust.method	The method used to adjust P-Values for multiple hypothesis testing. Default is 'BY'. See ?p.adjust for more details.

Value

A numeric vector of P-Values adjusted to multiple hypothesis testing. Names are the annos.2.test.

asishallab/GeneFamilies documentation built on May 22, 2023, 11:30 a.m.