Hi, I'm totally new to the field, I've never used R before, but I need to normalize some expression data. In every file I have many columns corresponding to different samples (different source cells) and rows corresponding to different genes. However I have many different files corresponding to different experiments and they have different total numbers of rows (genes). I want to use RLE normalization to normalize all of the data, which is implemented in the function calcNormFactors from the package edgeR, but I don't understand how can I put the read counts into a matrix since my files contain different numbers of genes (rows). I thought I should have a giant matrix containing data from all of my files where the columns are the samples and rows are the genes. Should I perhaps take the file that has the highest number of genes and input "0" for these genes if they are not present in the other files? Thanks for your time. Jan [[alternative HTML version deleted]]