ppiPre (version 1.9)

ComputeAllEvidences: Compute the Biological and Topological Similarities Between Protein Pairs

Description

Given an input file, this function will calculate 4 biological and 3 topological similarities between each protein pair in the file.

Usage

ComputeAllEvidences(input,output="AllEvidences-ppiPre.csv",organism="yeast", drop ="IEA", header=TRUE, sep=",")

Arguments

input
CSV format PPI network, each line of which includes two interacting proteins and another column which is 1 or 0 indicating that the interaction is positive or negative.
output
Result will be saved in the output file.
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.
header
If the input file contains header.
sep
The separator of the input file.

References

[1] S. Benabderrahmane, M. Smail-Tabbone, O. Poch, A. Napoli, and M.-D. Devignes, "IntelliGO: a new vector-based semantic similarity measure including annotation origin", BMC Bioinformatics, vol. 11, no. 1, p. 588, 2010.

[2] J. Z. Wang, Z. Du, R. Payattakool, P. S. Yu, and C.-F. Chen, "A new method to measure the semantic similarity of GO terms", Bioinformatics, vol. 23, no. 10, pp. 1274-1281, May. 2007.

[3] 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.

[4] T. Zhou, L. Lv, and Y.-C. Zhang, "Predicting missing links via local information", The European Physical Journal B - Condensed Matter and Complex Systems, vol. 71, no. 4, pp. 623-630, Oct. 2009

[5] L. A. Adamic and E. Adar, "Friends and neighbors on the Web", Social Networks, vol. 25, no. 3, pp. 211-230, 2003.

[6] P. Jaccard, "Etude comparative de la distribution florale dans une portion des Alpes et des Jura", Bull. Soc. Vaud. Sci. Nat, vol. 37, p. 541, 1901.

[7] M. Kanehisa and S. Goto, "KEGG: Kyoto Encyclopedia of Genes and Genomes", Nucleic Acids Research, vol. 28, no. 1, pp. 27 -30, 2000.

[8] 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

TCSSGeneSim IntelliGOGeneSim GOKEGGSims

Examples

Run this code
  #edges <- data.frame(node1=c("1132", "1133", "1134", "1134", "1145", "1147"),
  #                    node2=c("1134", "1134", "1145", "1147", "1147", "1149"),
  #                    label=c(1, 1, 1, 0, 0, 0))
  #graph<-igraph::graph.data.frame(edges,directed=FALSE)
  #samplefile <- "ppiPre-ComputeAllEvidences-sample.csv"
  #write.csv(edges,file=samplefile,row.names=FALSE) 
  #ComputeAllEvidences(input=samplefile,output="AllEvidences-ppiPre.csv",organism="human") 
  #result<-read.csv(file="AllEvidences-ppiPre.csv")
  #print(result)

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