I am a bit confused about the statistics for paired samples in edgeR.
I have 4 different treatments, A, B, C and D, each one with 4 samples. 2 of those samples are "before" treatment and the other 2 are "after" treatment.
If iam correct, checking the edgeR manual, the design of the model matrix should be:
> groups <- factor(targets$Group) > treatment <- factor(targets$Treatment, levels=c("before","after")) > design <- model.matrix(~groups+treatment)
But in the case I have a data that is a simple table containing the genes in the first column and de samples in the other columns, how can I construct the model matrix to accept this table format?
I think I can simple open the table as a matrix and atributte the factors to the samples:
> my_table <- data.matrix(my_table, row.names.default(my_table)) > groups <- factor(c(A1,A2,A3,A4,B1,B2,B3,B4,C1,C2,C3,C4,D1,D2,D3,D4)) > treatment <- factor(c("before", "before", "after", "after","before", "before", "after", "after","before", "before", "after", "after",)) > design <- design.matrix(~groups+treatment) > y <- DGEList(counts=my_table, group=groups)
But I don't know if this is correct.
Does anyone can help with that, I'd really appreciate it.