label_prop_gsea {gsean} | R Documentation

## Over-representaion analysis with the label propagation algorithm

### Description

ORA is performed by GSEA with the label propagation algorithm

### Usage

    label_prop_gsea(geneset, x, adjacency, threshold = 0.99, nperm = 1000,
                    minSize = 1, maxSize = Inf, gseaParam = 1, nproc = 0,
                    BPPARAM = NULL, ...)

### Arguments

`geneset` | list of gene sets
`x` | set of genes
`adjacency` | adjacency matrix
`threshold` | threshold of correlation for nodes to be considered neighbors (default: 0.99)
`nperm` | number of permutations (default: 1000)
`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
`...` | additional parameters for label propagation; see RANKS::label.prop

### Value

GSEA result

### Author(s)

Dongmin Jung

### See Also

fgsea::fgsea, RANKS::label.prop

### Examples

    data(examplePathways)
    data(exampleRanks)
    exampleRanks <- exampleRanks[1:100]
    geneNames <- names(exampleRanks)
    set.seed(1)
    x <- sample(geneNames, 10)
    adjacency <- diag(length(exampleRanks))
    rownames(adjacency) <- geneNames
    result.GSEA <- label_prop_gsea(examplePathways, x, adjacency)

[Package gsean version 1.6.0 Index]