KEGGpredict-methods: Predict KEGG pathway annotations for proteins

In PANDA: Preferential Attachment Based Common Neighbor Distribution Derived Functional Associations

Description

This function uses a direct annotation scheme to predict KEGG pathway annotations for proteins in the network derived with the PAND algorithm.

Usage

KEGGpredict(Pfile, PPIdb, Gene2Annotation, p_value=0.001, IDtoNAME)

Arguments

Pfile	A data frame returned from the function "SignificantPairs"
PPIdb	A 2-column data frame consisting of binary interactions where each row i.e. c(A, B) represents an undirected edge (interaction) between gene A and gene B.
Gene2Annotation	A list that maps KEGG pathway ID to genes. The names should be gene symbols and the elements should be KEGG pathways. i.e. $IGSF5 [1] "hsa04530" "hsa05120" $OR2T8 [1] "hsa04740" $hCG_1776980 [1] "hsa00020" "hsa00190" "hsa01100" "hsa05010" "hsa05012" "hsa05016" ......
p_value	A cut-off for p-values from Fishers exact test when predicting KEGG pathway annotations
IDtoNAME	A table that maps KEGG pathway ID to KEGG pathway names.

Value

This function returns a data frame with column names: "Symbol", "KEGGID", "PathName", "Ratio" and "Pvalue". "Symbol" is the name of the node this function predicts KEGG annotation for. "KEGGID" and "PathName" are the predicted KEGG pathway identifier and the pathway name, respectively. "Ratio" is the proportion of neighboring nodes that have the predicted KEGG annotation. "Pvalue" is calculated from the "Ratio" by Fishers exact test.

See Also

SignificantPairs, ProteinCluster, GOpredict, SignificantSubcluster

PANDA documentation built on May 2, 2019, 6:53 a.m.