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##' use limma function to get pvalue
##'
##' use limma function to get pvalue
##' @title use limma function to get pvalue
##' @param astudy A list contains a data matrix and a vector of group label
##' @return A list of pvalue and effect size
##' @author Zhiguang Huo
##' @import limma
##' @export
##' @examples
##'
##' N0 = 10
##' G <- 1000
##' GDEp <- 50
##' GDEn <- 50
##'
##' set.seed(15213)
##'
##' 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,caseLabel] - 2
##'
##' alabel <- c(rep(0,length(ControlLabel)),rep(1,length(caseLabel)))
##' Study <- list(data=astudy, label=alabel)
##'
##' result <- function_limma(Study)
##' fdr <- p.adjust(result$pvalue)
##' sum(fdr<=0.05)
##'
function_limma <- function(astudy) {
alabel <- astudy$label
aData <- astudy$data
adesign = cbind(rep(1, length(alabel)), alabel)
afit <- lmFit(aData, adesign)
afit <- eBayes(afit)
aeffectsize <- afit$coefficients[, 2]
apvalue <- afit$p.value[, 2]
return(list(pvalue = apvalue, effectSize = aeffectsize))
}
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