performGSVA: Gene set variation analysis

In TNBC.CMS: TNBC.CMS: Prediction of TNBC Consensus Molecular Subtypes

Description

Performs GSVA on gene sets. Also draws a heatmap representing GSVA scores.

Usage

performGSVA(expr, pred, gene.set = NULL, gsva.kcdf = "Gaussian")

Arguments

expr	A SummarizedExperiment object or a matrix containig gene expression profiles. If input is a SummarizedExperiment, the first element in the assays list should be a matrix of gene expression. Rows and columns of the gene expression matrix correspond to genes and samples, respectively (rownames must be to gene symbols).
pred	A vector of predicted consensus molecular subtypes.
gene.set	Gene sets provided as a list. If NULL, the hallmark pathway gene sets are used.
gsva.kcdf	Kernel to be used in the estimation of the cumulative distribution function. By default, this is set to "Gaussian" which is suitable for continuous expression values. If expression values are counts, "Poisson" is recommended.

Details

This is a wrapper function of the gsva function in the GSVA package to compute GSVA enrichment scores per sample and produce a heatmap comparing them across consensus molecular subtypes.

Value

A matrix of GSVA enrichment scores.

References

Liberzon, A. et al. (2015). The molecular signatures database hallmark gene set collection. Cell systems, 1, 417-425.

Examples

# Load gene expression profiles of TNBC samples
data(GSE25055)

# Predict consensus molecular subtypes of TNBC samples
prediction <- predictCMS(expr = GSE25055)

# Perform GSVA on the hallmark pathway gene sets
resultGSVA <- performGSVA(expr = GSE25055, pred = prediction)

TNBC.CMS documentation built on Nov. 8, 2020, 7:53 p.m.