geneSetsStats: Summarizes useful statistics per gene set from a...

Description Usage Arguments Value Examples

View source: R/MultiGSEAResult-methods.R

Description

This function calculates the number of genes that move up/down for the given contrasts, as well as mean and trimmed mean of the logFC and t-statistics. Note that the statistics calculated and returned here are purely a function of the statistics generated at the gene-level stage of the analysis.

Usage

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geneSetsStats(
  x,
  feature.min.logFC = 1,
  feature.max.padj = 0.1,
  trim = 0.1,
  reannotate.significance = FALSE,
  as.dt = FALSE
)

Arguments

x

A MultiGSEAResult object

feature.min.logFC

used with feature.max.padj to identify the individual features that are to be considered differentially expressed.

feature.max.padj

used with feature.min.logFC to identify the individual features that are to be considered differentially expressed.

trim

The amount to trim when calculated trimmed t and logFC statistics for each geneset.

Value

A data.table with statistics at the gene set level across the prescribed contrast run on x. These statistics are independent of any particular GSEA method, but rather summarize aggregate shifts of the gene sets individual features. The columns included in the output are summarized below:

Examples

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vm <- exampleExpressionSet(do.voom=TRUE)
gdb <- exampleGeneSetDb()
mg <- multiGSEA(gdb, vm, vm$design, 'tumor')
head(geneSetsStats(mg))

lianos/multiGSEA documentation built on Nov. 17, 2020, 1:26 p.m.