differentialPathwayAnalysis: Differential Expression Analysis For Pathways

In pouryany/PanomiR: Detection of miRNAs that regulate interacting groups of pathways

Differential Expression Analysis For Pathways

Description

Performs differential expression analysis for pathways using LIMMA package with gene counts

Usage

differentialPathwayAnalysis(
  geneCounts,
  pathways,
  covariates,
  condition,
  adjustCovars = NULL,
  covariateCorrection = FALSE,
  quantileNorm = FALSE,
  outDir = ".",
  saveOutName = NULL,
  id = "ENSEMBL",
  deGenes = NULL,
  minPathSize = 10,
  method = "x2",
  trim = 0.025,
  geneCountsLog = TRUE,
  contrastConds = NA
)

Arguments

geneCounts	Gene counts, rows refer to genes and columns to samples.
pathways	Pathways table, containing pathway names and genes with id specified.
covariates	Covariates/metadata file; rows matches the columns of geneCounts.
condition	Condition to be examined (tumor vs normal etc); must exist in covariates column.
adjustCovars	Adjustment covariates like batch; if NULL, no adjustments performed.
covariateCorrection	If TRUE, performs covariates detection and correction; requires **adjustCovars**; (limma).
quantileNorm	If TRUE, performs quantile normalization on pathway summary statistics; from *preprocess* package.
outDir	Output directory.
saveOutName	If not NULL, saves output as RDS using save name, if NULL, does not save output.
id	ID matching genes to pathways; rownames of geneCounts.
deGenes	If not NULL, add t-scores to pathways summary statistics; filter by genes t-scores.
minPathSize	Minimum pathway size.
method	Define method to use for pathway summary statistics; specifications in documentations.
trim	Filter pathways with mean less than trim threshold in pathway summary statistics.
geneCountsLog	If TRUE, log(geneCounts).
contrastConds	Provide a contrast expression to be used in Limma comparison. This is necessary if you have more than two levels in the condition covariate.

Value

List containing differentially expressed pathways as DEP and pathway summary statistics as pathwaySummaryStats.

Examples

data("path_gene_table")
data("miniTestsPanomiR")

differentialPathwayAnalysis(geneCounts = miniTestsPanomiR$mini_LIHC_Exp,
pathways =  path_gene_table,
covariates = miniTestsPanomiR$mini_LIHC_Cov,
condition = 'shortLetterCode')

pouryany/PanomiR documentation built on Aug. 20, 2022, 11:17 p.m.