Description Usage Arguments Author(s) References See Also Examples
View source: R/TopologicSims.r
User can predict false negative interactions from an given PPI network, based on one to three topological similarities.
1 2 |
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. |
Yue Deng <anfdeng@163.com>
[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.
1 2 3 4 5 6 7 | 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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