Hello Bioconductor mailing list,
I'm using edgeR to analyze RNA-seq and RIP-seq data. I'm using the
moderated gene-wise dispersion method where I choose a prior.n based upon
the number of samples I have and how much shrinkage I desire to reduce
variance in my data. I've followed the R user guide and a guide a professor
made at my university to achieve gene-wise (tag-wise) dispersion as opposed
to common dispersion. I can see that the tag-wise dispersion changes for
each gene when I change the prior.n value (see below). However I notice
that that p-values and logFC values don't change when I change the prior.n
(see below).

So I'm wondering if I'm doing something wrong or if the p-values and/or
logFC are not supposed to change? Or is it just some data is not effected
at all by prior.n?

The following is an example of my command line code analyzing some RNA-seq
data. I illustrated an example where I used a prior.n = 1 or 4 to
illustrate how I don't see a change in the final results. Is this correct?
Thanks
J


normFact = calcNormFactors(TotalReads)

treatments = substr(colnames(TotalReads), 1, 3)

d = DGEList(counts = TotalReads, group = treatments, genes =
rownames(TotalReads), lib.size = colSums(TotalReads) * normFact)

d = estimateCommonDisp(d)

d$common.dispersion

[1] 0.1669584


#comparing prior.n 1 v. 4

d1 = estimateTagwiseDisp(d, prior.n  = 1)

d1

$tagwise.dispersion

[1] 0.1607020 0.3674590 0.1058665 0.1080470 0.1545314

20684 more elements ...

d4 = estimateTagwiseDisp(d, prior.n  = 4)

d4

$tagwise.dispersion

[1] 0.1463446 0.4059551 0.1278219 0.1213169 0.2150826

20684 more elements ...


#prior.n = 1

edgeHSMvHSFd1 = exactTest(d1, pair = c("HSM", "HSF"), (common.disp = FALSE
))


head(edgeHSMvHSFd1)

An object of class "DGEExact"

$table

                      logFC    logCPM       PValue

ENSG00000000003 -0.07130289  6.290327 6.073496e-01

ENSG00000000005 -2.28060195 -4.439294 1.000000e+00

ENSG00000000419  0.25083103  4.119127 8.780027e-02

ENSG00000000457 -0.19453270  4.557886 8.468506e-02

ENSG00000000460 -0.05015655  1.770160 9.075606e-01

ENSG00000000938  0.92221495  4.526491 1.227442e-11


#prior.n = 4

edgeHSMvHSFd4 = exactTest(d4, pair = c("HSM", "HSF"), (common.disp = FALSE
))


head(edgeHSMvHSFd4)

An object of class "DGEExact"

$table

                      logFC    logCPM       PValue

ENSG00000000003 -0.07130289  6.290327 6.073496e-01

ENSG00000000005 -2.28060195 -4.439294 1.000000e+00

ENSG00000000419  0.25083103  4.119127 8.780027e-02

ENSG00000000457 -0.19453270  4.557886 8.468506e-02

ENSG00000000460 -0.05015655  1.770160 9.075606e-01

ENSG00000000938  0.92221495  4.526491 1.227442e-11


sum(edgeHSMvHSFd1$table[,1]>0)

[1] 12770

sum(edgeHSMvHSFd4$table[,1]>0)

[1] 12770

#same results for DE genes for both

sum(edgeHSMvHSFd1$table[,1]>0 & edgeHSMvHSFd1$table[,3]<0.01)

[1] 1763

sum(edgeHSMvHSFd4$table[,1]>0 & edgeHSMvHSFd4$table[,3]<0.01)

[1] 1763

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