R/OriginxyCall.R

In RankProd: Rank Product method for identifying differentially expressed genes with application in meta-analysis

"OriginxyCall" <- function (data,cl,origin,sum = FALSE){
lev <- unique(cl)
uni.cl <- length(lev)
if (uni.cl > 2 ) stop("There is something wrong with the classlabels")
ori.lev <- unique(origin)
uni.ori <- length(ori.lev)
cat(" The data is from ",uni.ori,"different origins \n \n")
if (min(ori.lev) != 1 | max(ori.lev) != uni.ori){
    cat("Warning: origins labels are not numbered from 1 to ",uni.ori,"\n","\n")
}
if(uni.cl == 1){
    if (sum) {
        cat("Rank Sum analysis for one-class case","\n","\n")
    } else { 
        cat("Rank Product analysis for one-class case","\n","\n")}
    if (lev != 1) {
    cat("warning: Expected classlabel is 1, cl will hus be set to 1.","\n","\n")
    cl=rep(1,length(cl)) }
    data2 <- NULL
    data1 <- vector("list",uni.ori)
    for ( c in 1:uni.ori) {data1[[c]] = data[,origin == ori.lev[[c]]]}}
if(uni.cl == 2){
    if (sum) {
        cat("Rank Sum analysis for two-class case","\n","\n")
    } else {
        cat("Rank Product analysis for two-class case","\n","\n")
        }
if(min(lev) != 0 | max(lev) != 1){
    cat("Warning: Expected classlabels are 0 and 1. cl will thus
            be set to 0 and 1.","\n","\n")
		cl[which(cl == min(lev))] <- 0 ##small one is assigned to 0
		cl[which(cl == max(lev))] <- 1 ##big one is assigned to 0
		}
data2 <- vector("list",uni.ori)
data1 <- vector("list",uni.ori)
for ( c in 1:uni.ori) {
    index1 <- which(origin == ori.lev[[c]] & cl == 0)           
    index2 <- which(origin == ori.lev[[c]] & cl == 1)
    if (length(index1) == 0 | length(index1) == 0){
stop("Error: data from different origins should contain data from both classs")
}
    data1[[c]] <- data[,index1]
    data2[[c]] <- data[,index2]
    rm(index1,index2) }
    }
list(data1 = data1,data2 = data2)
}