GOSim (version 1.10.0)

getTermSim: Get pairwise GO term similarities.

Description

Returns the pairwise similarities between GO terms. Different calculation method are implemented.

Usage

getTermSim(termlist, method = "relevance", verbose = FALSE)

Arguments

termlist

character vector of GO terms

method

one of the supported methods for GO term similarity (see below)

verbose

print out various information or not

Value

• n x n matrix (n = number of GO terms) with similarities between GO terms scaled to [0,1]. If a GO term does not exist for the currently set ontology, the similarity is set to "NA".

Details

Currently the following methods for computing GO term similarities are implemented: [object Object],[object Object],[object Object],[object Object],.,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

References

[1] P. Resnik, Using Information Content to evaluate semantic similarity in a taxonomy, Proc. 14th Int. Conf. Artificial Intel., 1995

[2] J. Jiang, D. Conrath, Semantic Similarity based on Corpus Statistics and Lexical Taxonomy, Proc. Int. Conf. Research in Comp. Ling., 1998

[3] D. Lin, An Information-Theoretic Definition of Similarity, Proc. 15th Int. Conf. Machine Learning, 1998

[4] F. Couto, M. Silva, P. Coutinho, Implementation of a Functional Semantic Similarity Measure between Gene-Products, DI/FCUL TR 03-29, Department of Informatics, University of Lisbon, 2003

[5] Couto, F.; Silva, M. & Coutinho, P., Semantic Similarity over the Gene Ontology: Family Correlation and Selecting Disjunctive Ancestors, Conference in Information and Knowledge Management, 2005

[6] Lerman G. & Shaknovich B., Defining Functional Distance using Manifold Embeddings of Gene Ontology Annotations, PNAS, 104(27): 11334 - 11339, 2007

[7] A. Schlicker, F. Domingues, J. Rahnenfuehrer, T. Lengauer, A new measure for functional similarity of gene products based on Gene Ontology, BMC Bioinformatics, 7, 302, 2006.

[8] C. Pesquita, D. Faria, H. Bastos, A. Falcao, F. Couto, Evaluating GO-based Semantic Similarity Measures, In: Proc. 10th Annual Bio-Ontologies Meeting 2007, 37 - 40, 2007

See Also

getMinimumSubsumer, getDisjCommAnc, setEnrichmentFactors, setOntology, load.diffusion.kernel

Examples

#\donttest{
 setOntology("BP")
 # Lin's method
 getTermSim(c("GO:0006955","GO:0007584"),method="Lin") 
# Couto's method combined with Jiang-Conrath distance
getTermSim(c("GO:0006955","GO:0007584"),method="CoutoJiangConrath") 

# set enrichment factors
setEnrichmentFactors(alpha=0.1,beta=0.5) 
getTermSim(c("GO:0006955","GO:0007584"),method="CoutoEnriched") 
#}