I have a question about finding differentially covered regions (coverage represents methylation level which goes from 0 to several thousands). I'm using enrichment based method which can be summarized with coverage per gene:
data <- matrix(sample(80), 20) # Genes in rows rownames(data) <- letters[1:20] colnames(data) <- c("group_A_tr1", "group_A_tr2", "group_B_tr1", "group_B_tr2")
data matrix each row represents a gene and each column represents a sample. There are two sample groups (A and B) with two technical replicates per each group. Problem is that we do not have any biological replicates.
My goal is to identify genes that are differentially methylated between two groups. I know that
DESeq2 can be used in analysis like this, however I don't have enough samples. Basically I'll need to compare only two columns (after averaging technical replicates).
What method would be appropriate to work with data like this? Is it possible to treat technical replicates as biological ones?