[syintel87]

Anyhow, I still wonder why my plot of (p-value,count) looks like zigzag. In normal case, doesn't this happen? Is this because of my unstable data set?

Also, p-value distribution does not look bad, of which figure I attached in the very first posting. Though p-value distribution looks proper, if the library size is too small, is my analysis not enough to make conclusion?

[syintel87]

If for most of your time points you have only a few ten thousand usable reads, because most of your reads were used up by host mRNA, you may have to little usable data and the thing to do might be to improve on the wet-lab side by finding a better way to separate worm from host tissue.

If you want to go on working with your data to see whether you can see at least a few things, maybe start by making scatter plot or raw counts (each sample against each other sample).

You pseudo-replication scheme is not that good, either: The general idea of inference in a two group comparison is to find genes that show stronger differences between groups than within groups. So, you are now looking for genes that change more strongly between T1 and T2 than between either egg and juvenile or between t1 and t2. Why should the changes from juvenile to t2 be stronger than from egg to juvenile?

In the first place, I dealt with 7 time points separately and ran edgeR without replicate. Though there was no replicate, among 21 pairwise tests, one pairwise test of "egg and juvenile" provided the clearest. Yes, I agree that there is no reason to say that changes from egg to juvenile can be ignored. However, in overall, the 21 results did not look good.

So, in order to have replicates, I just cut lines between time points so that I could have at least two replicates. You mean this is unpersuadable and inappropriate, so that I need to find another way?