[BioC] (stupid) question about wilcoxon test and finding
naomi at stat.psu.edu
Tue Feb 15 21:56:54 CET 2005
When there is no differential expression (and if the genes were
independent) then the p-values should be uniformly distributed. So, if you
test at level alpha and you have N genes, you SHOULD find alpha*N genes
that have significant results (and all are false positives).
The FDR correction does 2 things simultaneously - it estimates the
percentage of genes that differentially express (using departures of the
p-values from the uniform distribution" - and then estimates the False
discovery rate for any observed p-value.
I guess we have to ask what "necessary" and "multiple testing"
mean. There are 2 kinds of error - false detects and false
non-detects. We do not do this type of correction if we worry more about
false non-detects. If false detects are a bigger problem, then the FDR
estimate allows us to estimate when we have an acceptable rate. If you are
really testing only a few genes on your arrays, I would not use FDR. If
you are really testing all the genes, then I think you have a "highly
multiple" testing situation.
I don't really like the term "adjusted p-value" for FDR estimates. They
are not probabilities, they are estimated error rates. But that issue was
discussed a few weeks ago on this list.
>so the next step is to correct the p values... i thought correcting p
>values is only necessary when i do multiple testing? sorry for my
>question, but i am more used to do some programming and work with
>databases then doing statistics...
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>>Naomi S. Altman 814-865-3791 (voice)
>>Bioinformatics Consulting Center
>>Dept. of Statistics 814-863-7114 (fax)
>>Penn State University 814-865-1348 (Statistics)
>>University Park, PA 16802-2111
Naomi S. Altman 814-865-3791 (voice)
Bioinformatics Consulting Center
Dept. of Statistics 814-863-7114 (fax)
Penn State University 814-865-1348 (Statistics)
University Park, PA 16802-2111
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