Nothing
IsoGenemSAM <- function(x, y, fudge.factor){
y <- as.matrix(y)
if(dim(y)[[1]]==1){
warning("There is only one gene in the data set.")
} 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))
# y.is.u <- t(apply(y.m, 1, function(x) isoreg(unx, x)$yf))
# y.is.d <- t(apply(y.m, 1, function(x) rev(isoreg(rev(unx), x)$yf)))
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) rev(pava(rev(x), w = rev(n.p)))))
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
direction <- ifelse(SSIS.u1 <= SSIS.d1, "u", "d")
iso.u = y.m
SSIS.dir= NULL
iso.u[direction=="u",] <- y.is.u[direction=="u",]
iso.u[direction=="d",] <- y.is.d[direction=="d",]
SSIS.dir[direction=="u"] <- SSIS.u1[direction=="u"]
SSIS.dir[direction=="d"] <- SSIS.d1[direction=="d"]
Esquare <- (SST0-SSIS.dir)/(SST0+fudge.factor[[1]])
n.pSum <- sum(n.p)
w <- (iso.u[,n.g] - y.m[,1]) / (sqrt(SST/(n.pSum-n.g)*(1/n.p[1] + 1/n.p[n.g])) + fudge.factor[[2]])
w.c <- (iso.u[,n.g] - iso.u[,1]) / (sqrt(SST/(n.pSum-n.g)*(1/n.p[1] + 1/n.p[n.g])) + fudge.factor[[3]])
m <- (iso.u[,n.g] - iso.u[,1]) / (sqrt(SSIS.dir/(n.pSum-n.g)) + fudge.factor[[4]])
i <- (iso.u[,n.g] - iso.u[,1]) / (sqrt(SSIS.dir/(n.pSum - apply(iso.u, 1, function(x) length(unique(x))))) + fudge.factor[[5]])
res <- list(E2 = Esquare,
Williams = as.numeric(w),
Marcus = as.numeric(w.c),
M = as.numeric(m),
ModM = as.numeric(i),
direction = direction)
return(res)
}
}
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