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ppiPre (version 1.7)

FNPre: Predict false negative interactions based on topological similarities

Description

User can predict false negative interactions from an given PPI network, based on one to three topological similarities.

Usage

FNPre(file,indicator=c("RA","AA","Jaccard"),threshold=0.1, 
      output="FalseNegativePreResult-ppiPre.csv")

Arguments

file
CSV format PPI network given by user, each line of which includes two interacting proteins.
indicator
Can be any combination of "RA", "AA", and "Jaccard", indicate the similarities used.
threshold
The ratio of false negative interactions to positive interactions in the network.
output
Result will be saved in the output file.

References

[1] 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 [2] L. A. Adamic and E. Adar, "Friends and neighbors on the Web", Social Networks, vol. 25, no. 3, pp. 211-230, 2003. [3] 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.

See Also

AASim JaccardSim RASim

Examples

Run this code
edges <- data.frame(node1=c("1132", "1133", "1134"),node2=c("1134", "1134", "1145"))
  graph<-igraph::graph.data.frame(edges,directed=FALSE)
  samplefile <- "ppiPre-FNPre-sample.csv"
  write.csv(edges,file=samplefile,row.names=FALSE) 
  FNPre(file=samplefile, indicator = c("RA", "AA"), threshold = 0.1)
  result<-read.csv(file="FalseNegativePreResult-ppiPre.csv")
  print(result)

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