[BioC] Behaviour of weights in limma

[Paul Harrison]

Hello,

I have some data from a variant of RNA-seq which I am hoping do some
moderated t-test differential testing on with limma. In this data,
many of the reads have sequenced through into the poly(A) tail, and we
believe this gives us information about changes in poly(A) tail
length.

For each gene and sample, we can calculate an average observed tail
length. It seems easy enough to calculate a standard error for this
average as well. In some cases we have few reads and the standard
error is high, in others we have quite a lot of reads and the standard
error is low.

What I'm hoping is that this can be translated into weights that can
be fed to limma to make it behave correctly. Do weights have some
specific meaning in terms of measurement variance? And how does this
interact with moderation between genes, for example could including
highly noisy measurements from some genes detract from the
significance of other genes where the measurement is more precise?


regards,
Paul Harrison

Victorian Bioinformatics Consortium / Monash University