Principal component analysis of gene expression microarray datasets

pca.r

my.data.frame <- read.delim("tab_delimited_file_with_probeset_ids_in_first_column.txt", row.names=1)
my.data.matrix <- as.matrix(my.data.frame)

# PCA by sample:
# center each gene (mean) without scaling
# scale each sample (root mean square) without centering
# transpose the matrix to PCA by sample instead of by gene

a <- scale(t(my.data.matrix), center=TRUE, scale=FALSE)
b <- scale(t(a), center=FALSE, scale=TRUE)
my.pca <- prcomp(t(b), center=FALSE)