[BioC] (stupid) question about wilcoxon test and finding
interesting genes
Naomi Altman
naomi at stat.psu.edu
Mon Feb 14 00:57:34 CET 2005
If I understand what you did, you should have only 1 column of p-values - 1
per gene. So, I think your apply command did not work as you expected
(although I think it should have).
My understanding is that you have 2 arrays per patient and took the 13 M
values. Applying a Wilcoxon test to each row should test that the median
difference is 0.
Try doing the test on a couple of rows and then compare with the output you
obtained.
After you get 1 p-value per gene, you should apply a multiple comparisons
adjustment. FDR is popular and can be computed using the "qvalue" library
in Bioconductor.
--Naomi
At 09:44 AM 2/11/2005, Dipl.-Ing. Johannes Rainer wrote:
>hi,
>i must excuse myself for my question, but i'm not really good in statistics...
>
>we have done affymetrix genechips with samples from patients before and
>after treatment. until now i searched for genes that are influenced by the
>treatment using M values but i wanted also to apply a statistical test to
>get some proof that the genes i found are significant.
>
>so i applied a wilcoxon paired test to the expression values (one test per
>gene). my samples size is 13 (13 chips with samples before treatment and
>13 afterwards). i subtracted the values after treatment from those before
>treatment (
>
>p.vals <- apply((untreated-treated),MARGIN=1,wilcox.test) , untreated is a
>matrix with 13 columns and 54000 rows (genes) and the same is treated).
>according to the p values i got nearly every gene is significant, also if
>the gene is not regulated.
>
>so my question, do i have to correct the p values or was i totally wrong
>with the assumption to get significant (and regulated) genes in this way?
>
>thanks
>
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Naomi S. Altman 814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics 814-863-7114 (fax)
Penn State University 814-865-1348 (Statistics)
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