clusterSim {GOSemSim} | R Documentation

## Semantic Similarity Between Two Gene Clusters

### Description

Given two gene clusters, this function calculates semantic similarity between them.

### Usage

    clusterSim(cluster1, cluster2, semData, measure = "Wang", drop = "IEA",
      combine = "BMA")

### Arguments

`cluster1` | A set of gene IDs.
`cluster2` | Another set of gene IDs.
`semData` | GOSemSimDATA object
`measure` | One of "Resnik", "Lin", "Rel", "Jiang" and "Wang" methods.
`drop` | A set of evidence codes based on which certain annotations are dropped. Use NULL to keep all GO annotations.
`combine` | One of "max", "avg", "rcmax", "BMA" methods, for combining semantic similarity scores of multiple GO terms associated with protein or multiple proteins assiciated with protein cluster.

### Value

similarity

### References

Yu et al. (2010) GOSemSim: an R package for measuring semantic similarity among GO terms and gene products Bioinformatics (Oxford, England), 26:7 976–978, April 2010. ISSN 1367-4803 http://bioinformatics.oxfordjournals.org/cgi/content/abstract/26/7/976 PMID: 20179076

### See Also

`goSim` `mgoSim` `geneSim` `mgeneSim` `mclusterSim`

### Examples

        d <- godata('org.Hs.eg.db', ont="MF", computeIC=FALSE)
        cluster1 <- c("835", "5261","241", "994")
    cluster2 <- c("307", "308", "317", "321", "506", "540", "378", "388", "396")
    clusterSim(cluster1, cluster2, semData=d, measure="Wang")

[Package GOSemSim version 2.8.0 Index]