gsean: Gene Set Enrichment Analysis with Networks

Description Usage Arguments Value Author(s) See Also Examples

View source: R/gsean.R

Description

GSEA or ORA is performed with networks from gene expression data

Usage

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gsean(geneset, x, exprs, pseudo = 1, threshold = 0.99, nperm = 1000,
      centrality = function(x) rowSums(abs(x)), weightParam = 1,
      minSize = 1, maxSize = Inf, gseaParam = 1, nproc = 0,
      BPPARAM = NULL, corParam = list(), tmax = 10, ...)

Arguments

geneset

list of gene sets

x

Named vector of gene-level statistics for GSEA or set of genes for ORA. Names should be the same as in gene sets.

exprs

gene expression data

pseudo

pseudo number for log2 transformation (default: 1)

threshold

threshold of correlation for nodes to be considered neighbors for ORA (default: 0.99)

nperm

number of permutations (default: 1000)

centrality

centrality measure, degree centrality or node strength is default

weightParam

weight parameter value for the centrality measure, equally weight if weightParam = 0 (default: 1)

minSize

minimal size of a gene set (default: 1)

maxSize

maximal size of a gene set (default: Inf)

gseaParam

GSEA parameter value (default: 1)

nproc

see fgsea::fgsea

BPPARAM

see fgsea::fgsea

corParam

additional parameters for correlation; see WGCNA::cor

tmax

maximum number of iterations for label propagtion (default: 10)

...

additional parameters for label propagation; see RANKS::label.prop

Value

GSEA result

Author(s)

Dongmin Jung

See Also

exprs2adj, label_prop_gsea, centrality_gsea

Examples

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data(examplePathways)
data(exampleRanks)
exampleRanks <- exampleRanks[1:100]
Names <- names(exampleRanks)
exprs <- matrix(rnorm(10*length(exampleRanks)), ncol = 10)
rownames(exprs) <- names(exampleRanks)
set.seed(1)
result.GSEA <- gsean(examplePathways, exampleRanks, exprs)

gsean documentation built on Nov. 8, 2020, 6:36 p.m.