wouldn't we try a correlation test better then ? On Wed, Jul 11, 2012 at 7:10 PM, Kevin R. Coombes wrote: > I can easily think of a reason for a one-sided test. Consider the case > where I have copy number data and gene expression data on a bunch of > samples, and I'd like to test whether changes in gene expression go the > same direction as changes in copy number. > > On 7/11/2012 8:21 AM, James W. MacDonald wrote: > >> Hi Alyaa, >> >> On 7/11/2012 2:59 AM, Alyaa Mahmoud wrote: >> >>> Hi All >>> >>> Is there a way to determine expression status of a gene (up, down) from >>> corrected p.values ? >>> >> >> No. The p-values are strictly between 0 and 1, so there is no way to >> discern the sign of the underlying t-statistic. This would not be true if >> you were doing a one-sided t-test, but I can't imagine a use case for a >> one-sided t-test in the context of microarray analysis. >> >> Best, >> >> Jim >> >> >> >>> Thanks a lot >>> Alyaa >>> >>> >> -- Alyaa Mahmoud "Love all, trust a few, do wrong to none"- Shakespeare [[alternative HTML version deleted]]