Dear all,
If I understand correctly, TMM-normalisation has two assumptions: 1. Most genes are not DE 2. Comparable number of DE genes that are up/down-regulated (i.e. symmetry)
According to my analysis (I am using limma-voom workflow), one of my contrasts yield 200 DEGs, 90% of which were upregulated. Does it mean that the assumptions break?
My second question: is it a good practice to review the previous steps in DE analysis after taking a look at the results?
Best regards, Mikhael
Thank you for the clarification. I got that understanding after reading this paper, particularly the "Normalization by distribution/testing" part.
Best regards, Mikhael
Most normalization methods will have some trouble, not be perfect, when there is a lot of asymmetric DE. But when I say "a lot", I mean as a percentage of the total number of genes, not as a proportion of the DE genes. Your experiment has very little asymmetry. If you have 180 up genes and 20 down genes, then the asymmetry is about 160 genes, which is a tiny percentage of the 10,000 - 20,000 genes that you are probably analysing. This small degree of asymmetry will not cause problems for any normalization method, much less for a very robust method like TMM. The paper you cite agrees that TMM is one of the best choices.