characteriseGeneset {vissE} | R Documentation

## Functionally characterise a list of genes

### Description

This function can be used to perform a network-based enrichment analysis of a list of genes. The list of genes are characterised based on their similarity with gene sets from the MSigDB. A network of similar gene sets is retrieved using this function.

### Usage

    characteriseGeneset(
      gs,
      thresh = 0.2,
      measure = c("ovlapcoef", "jaccard"),
      gscolcs = c("h", "c2", "c5")
    )

### Arguments

`gs` | a GeneSet object, representing the list of genes that need to be characterised.
`thresh` | a numeric, specifying the threshold to discard pairs of gene sets.
`measure` | a character, specifying the similarity measure to use: `jaccard` for the Jaccard Index and `ovlapcoef` for the Overlap Coefficient.
`gscolcs` | a character, listing the MSigDB collections to use as a background (defaults to h, c2, and c5). Collection types can be retrieved using `msigdb::listCollections()`.

### Value

an igraph object, containing gene sets that are similar to the query set. The network contains relationships between results of the query too.

### Examples

    library(GSEABase)
    data(hgsc)

    #create a geneset using one of the Hallmark gene sets
    mySet <- GeneSet(
      geneIds(hgsc[[2]]),
      setName = 'MySet',
      geneIdType = SymbolIdentifier()
    )

    #characterise the custom gene set
    ig <- characteriseGeneset(mySet)
    plotMsigNetwork(ig)

[Package vissE version 1.0.0 Index]