mclusterSim {GOSemSim} | R Documentation

## Pairwise Semantic Similarities for a List of Gene Clusters

### Description

Given a list of gene clusters, this function calculates pairwise semantic similarities.

### Usage

    mclusterSim(clusters, semData, measure = "Wang", drop = "IEA", combine = "BMA")

### Arguments

`clusters` | A list of gene clusters.
`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 matrix

### 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` `clusterSim`

### Examples

     d <- godata('org.Hs.eg.db', ont="MF", computeIC=FALSE)
     cluster1 <- c("835", "5261","241")
     cluster2 <- c("578","582")
     cluster3 <- c("307", "308", "317")
     clusters <- list(a=cluster1, b=cluster2, c=cluster3)
     mclusterSim(clusters, semData=d, measure="Wang")

[Package GOSemSim version 2.16.1 Index]