Hi, I'm trying to create a design matrix for the analysis of differentially expressed genes from microarray data using limma. However, my code generates a matrix with fewer samples than the number of arrays I have in my data frame and therefore I can't run a Bayes fit on this data.
I have some NA's in my data set that does not fit within the levels MU or WT, could this be what's going wrong? and if so can anyone suggest any ideas?
Many thanks!
treatment <- factor(clinical$treatment, levels=c("MU", "WT"))
#clinical is a csv file which cointains details of the microarray (including file names and treatment)
design <- model.matrix(~0+treatment)