weightedKS_ofCSEA: Calculate weighted random walk k-s test for CSEA

In wangxlab/uniConSigPreCal: Fast calculation of uniConSig and CSEA

Description

calculate normalized enrichment score based on weighted gene list(weights), on-set gene set(positiveList), and permutation result(myPermu).

Usage

weightedKS_ofCSEA(weights, positiveList, myPermu, nPermu = 1000)

Arguments

weights	A vector of weights. The name of each value in the vector is it's Entrez gene ID
positiveList	A list of list containing pathways of genes. Each sublist is a pathway (or a concept), containing Entrez gene IDs
myPermu	A list of list containing permutations of randomly selected genes for each pathway.
nPermu	The number of permutations used throughout the calculations

Value

A table of 3 columns, "pathway names","NES","pValue"

Examples

##For a "result" calculated from cal_uniConSig:
weight.call<-c(0.1,0.2,0.5,0.7,0.9,1)
names(weight.call)<-1:6
pathway.my<-list()
pathway.my[[1]]<-1:10
pathway.my[[2]]<-5:15
myPermu.call<-construct_permuList(weight.call,pathway.my)
myNES<-weightedKS_ofCSEA(weight.call,pathway.my,myPermu.call)

wangxlab/uniConSigPreCal documentation built on May 23, 2019, 9:31 a.m.