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...(samples). I did unsupervised clustering using pvclust to get 4 classes. What I would like to do is to get unique genes for each class which can best characterize them. I did so and had the problem when running the code. The error message is: > rf.vs1 <- varSelRF(exprSet, cl, ntree = 200, ntreeIterat = 100, vars.drop.frac = 0.2) error in randomForest.default(x = xdata, y = Class, ntree = ntree, mtry = mtry, : length of response must be the same as predictors My code is: library(varSelRF) exprSet <- as.matrix(read.table('varSelRF_x.txt',header = FALSE)) cl <- factor(c(re...