gsean {gsean} | R Documentation

## Gene Set Enrichment Analysis with Networks

### Description

GSEA or ORA is performed with networks from gene expression data

### Usage

    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

    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)

[Package gsean version 1.6.0 Index]