R/Isomean.R

In IsoGeneGUI: A graphical user interface to conduct a dose-response analysis of microarray data

`Isomean` <-
function (x,y)
{

  if(dim(y)[[1]] == 1){
    
    temp2 <- pava(tapply(y, x, mean))
    temp3 <- rbind(temp2,temp2)
    temp4 <- temp3[1,,drop=FALSE]
	temp5 <- unname(temp4)
	
    return(temp5)
  } else {
    
    ordx <- order(x)
    x <- x[ordx]
    y <- y[, ordx]
    unx <- unique(x)
    ydf <- as.data.frame(t(y))
    y.m <- do.call("cbind", unclass(by(ydf, x, colMeans)))
    y.m.tot <- matrix(rep(rowMeans(y), length(x)), ncol = length(x))
    n.p <- table(x)
    n.g <- length(n.p)
    y.is.u <- t(apply(y.m, 1, function(x) pava(x, w = n.p)))
    y.is.d <- t(apply(y.m, 1, function(x) pava(x, w = n.p, decreasing = TRUE)))
    rep.iso.d <- y.is.d[, rep(1:length(n.p), n.p)]
    rep.iso.u <- y.is.u[, rep(1:length(n.p), n.p)]
    y.m.all <- y.m[, rep(1:length(n.p), n.p)]
    SST0 <- rowSums((y - rowMeans(y))^2)
    SSIS.u1 <- rowSums((rep.iso.u - y)^2)
    SSIS.d1 <- rowSums((rep.iso.d - y)^2)
    SST <- rowSums((y - y.m.all)^2)
    direction = NULL
    iso.dir <- ifelse(SSIS.u1 <= SSIS.d1, "u", "d")
    iso.mean <- matrix(0,nrow(y),length(unx))
    for (i in 1: nrow(y)) {
      if (iso.dir[i]=="u"){
        iso.mean[i,] <- y.is.u[i,]
      } 
      else {
        iso.mean[i,] <- y.is.d[i,]
      }
    }
    return(iso.mean )
    
  }     
  
        
}