[BioC] Multiple test question in micrarray- FDR

Wayne Xu wxu at msi.umn.edu
Sat Dec 13 18:36:08 CET 2008

I am not sure this is a right place to ask this question, but it is 
about micrarray data analysis:

In two group t test, the multiple test Q values are depending on the 
total number of genes in the test. If I filter the gene list first, for 
example, I only use those genes that have1.2 fold changes for T test and 
multiple test, this gene list is much smaller than the total gene list, 
then the multiple test q values are much smaller.

Do you think above is a correct way? People who do not do that way may 
consider the statistical power may be lost? But how much power lost and 
how to calculate the power in this case?

When people report multiple test Q values, they usually do not mention 
how many genes are used in this multiple test. You can get different Q 
values (even use the same method, e.g. Benjamin and Holm adjust method) 
in the same dataset. Then how can it make sense if the same genes have 
different Q values?

Can some experts explain this or point to somewhere I can find the answer?

Thanks in advance,


More information about the Bioconductor mailing list