Dear all,
I am confused about how t-test or F-test is implemented in limma/edgeR.
Let's say I have a small dataset: two conditions, each condition has 3 replicates, and there are 4 genes.
Con1 rep1 | Con1 rep2 | Con1 rep3 | Con2 rep1 | Con2 rep2 | Con2 rep3 |
gene1 | |||||
gene2 | |||||
gene3 | |||||
gene4 |
My questions is if I use limma/edgeR to analyze the DEGs across the two conditions, does limma first use the regular t-test to calculate if the mean of con1 is significantly different from the mean of con2 for each gene independently? And gets a regular t-statistic? Then use eBayes to adjust the regular t statistic and get the moderated t?
Look forward to your reply.
Regards.
If it does not work like I said, is the DEG calculation process in limma/edgeR essentially based on t-test/F-test? If not, what test is the foundation?
Regards.
Yes, the tests in limma are closely analogous to ordinary t-tests and F-tests and can be thought of as equivalent to them when you make conclusions.
That is all explained in the limma documentation and in the references that I listed. See for example Chapter 13 of the limma User's Guide. Even just reading the ?eBayes help page would give you some pointers as to the relationship between ordinary t-tests and moderated t-tests.
Thank you very much, got it!
Regards.