[BioC] decideTests with nestedF
James W. MacDonald
jmacdon at med.umich.edu
Fri Jun 16 17:29:36 CEST 2006
Pedro López Romero wrote:
> Hi Jim, thank you so much for the replay.-
> I am not using decideTests ( ) to filter the genes. I am using p.adjust ()
> ord=which(p.adjust(fit2$F.p.value,method="fdr") < 0.05)
> Then, I use the list of genes that result to be significant to apply
> decideTests (..., method="separate"). I thought that this could be
> conceptually similar as using decideTests (..., method="nestedF").
> I understand that "nestedF" follows a step-wise procedure selecting first
> genes using their moderated F-statistic, and second (for the selected gene)
> selecting the contrast that contributes to the significance of the F by the
> largest value of their moderated t-statistics. I think that this is clear to
> me. As a matter of fact you explained this recently:
> So now, instead of using "nestedF", why is not possible to select genes in a
> two-step-wise procedure?, firstly using a F-test to select genes that are
> differentially expressed in at least one contrast and from this list of
> selected-genes, to select the genes that are significant contrast by
> contrast. It would be similar to nestedF, but instead of selecting the
> contrast by the largest t-statistic, I perform a t-statistic for the whole
> set of "selected-F-genes" for every contrast.
This is the conventional method for analyzing data with ANOVA. You first
fit the ANOVA model, then if it is significant based on the F-statistic,
you look at contrasts to see which contrast(s) contributed to the
result. In other words, I don't think there is a reason you couldn't do
things this way.
> On the other hand, when using "nestedF" I get some genes with a 0.9 adjusted
> p-value, that probably should not be considered as diferentially expressed.
Not sure I understand your point. Are you saying that a particular
contrast that appears to be significant using your method ends up having
a very large p-value if you use nestedF?
James W. MacDonald, M.S.
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
Ann Arbor MI 48109
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