getGeneSim {GOSim}R Documentation

Compute functional similarity for genes.

Description

Calculate the pairwise functional similarities for a list of genes using different strategies.

Usage

getGeneSim(genelist, similarity = "OA", similarityTerm = "JiangConrath", normalization = TRUE, verbose = TRUE)

Arguments

genelist character vector of Entrez gene IDs
similarity method to calculate the functional similarity between gene products
similarityTerm method to compute the similarity of GO terms
normalization normalize the similarities to [0,1] by transforming sim(x,y) <- sim(x,y)/sqrt(sim(x,x)*sim(y,y))
verbose print out some information

Details

The method to calculate the pairwise functional similarity between gene products can either be: begin{ldescription}

"max"
the maximum similarity between any two GO terms
"mean"
the average similarity between any two GO terms
"OA"
the optimal assignment (maximally weighted bipartite matching) of GO terms associated to the gene having fewer annotation to the GO terms of the other gene.
end{ldescription}

Value

n x n similarity matrix (n = number of genes)

Note

The result depends on the currently set ontology.

Author(s)

Holger Froehlich

References

H. Froehlich, N. Speer, C. Spieth, and A. Zell, Kernel Based Functional Gene Grouping, Proc. Int. Joint Conf. on Neural Networks (IJCNN), 6886 - 6891, 2006

See Also

getGeneSimPrototypes, getTermSim, setOntology

Examples

        # see evaluateClustering

[Package GOSim version 1.0.2 Index]