groupedGSEAtoStackedReport: Build a report from gene set enrichment results.

In calebclass/NanoTube: An Easy Pipeline for NanoString nCounter Data Analysis

Build a report from gene set enrichment results.

Description

After clustering FGSEA results by gene set similarity, this function builds a report containing the individual gene expression profiles for genes contained in each gene set cluster.

Usage

groupedGSEAtoStackedReport(grouped.gsea, leadingEdge, de.fit, outputDir = NULL)

Arguments

grouped.gsea	Output from groupFGSEA()
leadingEdge	Leading edge analysis results used in groupFGSEA()
de.fit	Differential Expression results from Limma or NanoStringDiff
outputDir	Directory for output files. If NULL (default), will return the stacked report instead of writing to a file.

Value

A stacked report containing statistics and gene expression profiles for genes contained in each cluster

Examples

data("ExamplePathways")
data("ExampleResults") # Results from runLimmaAnalysis

fgseaResults <- limmaToFGSEA(ExampleResults, gene.sets = ExamplePathways,
                             min.set = 5, rank.by = "t")
leadingEdge <- fgseaToLEdge(fgseaResults, cutoff.type = "padj", cutoff = 0.1)

fgseaGrouped <- groupFGSEA(fgseaResults$Autoimmune.retinopathy, 
                            leadingEdge$Autoimmune.retinopathy,
                            join.threshold = 0.5,
                            dist.method = "binary")

results.AR <- groupedGSEAtoStackedReport(
              fgseaGrouped,
              leadingEdge = leadingEdge$Autoimmune.retinopathy,
              de.fit = ExampleResults)

calebclass/NanoTube documentation built on Nov. 21, 2023, 12:31 p.m.