View source: R/variabilityIndex.r
| variabilityIndex | R Documentation |
Variability Index
variabilityIndex(studies, afunction, B = 10, silence = FALSE)
studies |
a list of K studies. Each element (kth study) of the list is another list consisting gene expression matrix and and label information. |
afunction |
A function for DE analysis. Options can be function_limma or function_edgeR. Default option is function_limma. However, use could define their own function. The input of afunction should be list(data, label) which is consistent with one element of the studies list/argument. The return of afunction should be list(pvalue=apvalue, effectSize=aeffectsize) |
B |
number of permutation should be used. B=1000 is suggested. |
silence |
If TRUE, will print out the bootstrapping procedure. |
Variability Index via boostrap AW weight.
A list consisting of biomarker categrorization result.
varibility |
Varibility index for all genes |
Zhiguang Huo
N0 = 10
G <- 1000
GDEp <- 50
GDEn <- 50
K = 4
studies <- NULL
set.seed(15213)
for(k in 1:K){
astudy <- matrix(rnorm(N0*2*G),nrow=G,ncol=N0*2)
ControlLabel <- 1:N0
caseLabel <- (N0 + 1):(2*N0)
astudy[1:GDEp,caseLabel] <- astudy[1:GDEp,caseLabel] + 2
astudy[1:GDEp + GDEn,caseLabel] <- astudy[1:GDEp + GDEn,caseLabel] - 2
alabel = c(rep(0,length(ControlLabel)),rep(1,length(caseLabel)))
studies[[k]] <- list(data=astudy, label=alabel)
}
result <- variabilityIndex(studies,function_limma,B=100)
head(result)
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