TCSSGeneSim: Topological Clustering Semantic Similarity(TCSS) Between two...

In ppiPre: Predict Protein-Protein Interactions Based on Functional and Topological Similarities

Description

Given two genes, this function will calculate the TCSS between them

Usage

TCSSGeneSim(gene1, gene2, ont = "MF", organism = "yeast", drop = "IEA")

Arguments

gene1	Entrez gene id.
gene2	Another entrez gene id.
ont	One of "MF", "BP", and "CC" subontologies.
organism	One of "anopheles", "arabidopsis", "bovine", "canine", "chicken", "chimp", "ecolik12", "ecsakai", "fly", "human", "malaria", "mouse", "pig", "rat", "rhesus", "worm", "xenopus", "yeast" and "zebrafish."
drop	A set of evidence codes based on which certain annotations are dropped. Use NULL to keep all GO annotations.

Value

geneSim	Semantic similarity.
GO1	Corresponding GO terms for gene1.
GO2	Corresponding GO terms for gene2.

Author(s)

Yue Deng <[e-mail]>

References

[1] S. Jain and G. Bader, "An improved method for scoring protein-protein interactions using semantic similarity within the gene ontology", BMC Bioinformatics, vol. 11, no. 1, p. 562, 2010.

[2] G. Yu, F. Li, Y. Qin, X. Bo, Y. Wu, and S. Wang, "GOSemSim: an R package for measuring semantic similarity among GO terms and gene products", Bioinformatics, vol. 26, no. 7, pp. 976-978, Apr. 2010.

See Also

IntelliGOGeneSim

Examples

  #TCSSGeneSim("1134", "1145", ont="MF", organism="human")
  #TCSSGeneSim("YOR065W", "YEL024W", ont="CC", organism="yeast", drop="IEA")

ppiPre documentation built on May 30, 2017, 4:33 a.m.