[BioC] Do my Limma results look "normal"?

[Paul Geeleher]

Hi,

This is the first time I've ever analyzed a microarray experiment
using Limma (or anything else for that matter) and I was hoping that
somebody could look at my results and tell me if they look normal.

The experiment is measuring differential expression between miRNAs of
HER2+ and HER2- breast cancer tissue. There are 3 HER2+ arrays and 4
HER2- arrays and each of the 399 miRNAs is replicated 4 times in each
array.

TopTable() reveals the following miRNAs with a fold change above 1.5,
which I thought was a reasonable cutoff:

                  ID     logFC         t      P.Value    adj.P.Val          B
273      hsa-miR-451 -4.645060 -8.226854 4.510441e-09 9.246404e-07 10.8484797
128      hsa-miR-205  3.551495  7.574564 2.370061e-08 3.239083e-06  9.2222865
13       hsa-miR-101 -2.310652 -6.569497 3.374177e-07 2.567796e-05  6.6146751
282      hsa-miR-486 -2.686910 -6.542808 3.626060e-07 2.567796e-05  6.5439656
55       hsa-miR-144 -2.890719 -5.889594 2.152998e-06 1.261042e-04  4.7952480
387      mmu-miR-463 -2.609257 -5.764143 3.042120e-06 1.559086e-04  4.4561920
388      mmu-miR-464 -2.080402 -5.696976 3.662006e-06 1.668247e-04  4.2743601
151      hsa-miR-223 -1.722956 -5.637290 4.318942e-06 1.770766e-04  4.1126276
51    hsa-miR-142-3p -3.262824 -5.397809 8.386312e-06 3.125807e-04  3.4626378
14   hsa-miR-101_MM1 -1.922710 -5.224075 1.358743e-05 4.175776e-04  2.9905370
159  hsa-miR-26b_MM2 -2.221853 -5.206724 1.425875e-05 4.175776e-04  2.9433849
236 hsa-miR-376a_MM1 -1.633555 -4.653220 6.637043e-05 1.700742e-03  1.4433277
266     hsa-miR-432*  1.512622  4.627293 7.131510e-05 1.719952e-03  1.3734422
168      hsa-miR-29b -1.954087 -4.198854 2.323860e-04 4.763912e-03  0.2280262
31  hsa-miR-126*_MM2 -1.537988 -3.209957 3.233842e-03 5.099520e-02 -2.2888897
52    hsa-miR-142-5p -1.881192 -2.831493 8.332384e-03 9.002153e-02 -3.1731794


Another person is sanity testing this data using GeneSpring and they
are getting much higher p-values compared to mine. They are also
taking the step of excluding quite a few of the miRNAs from the
experiment based on their standard deviation across the arrays of each
group. Should I be doing this also or is this taken into account by
the eBayes() function or lmFit()?

If you are interested the script I wrote to do the analysis is here:
http://article.gmane.org/gmane.science.biology.informatics.conductor/18032/match=miRNA

Thanks for any advice,

-Paul.