[BioC] Methods in decideTests (limma)
Gordon K Smyth
smyth at wehi.EDU.AU
Fri Jun 5 03:47:05 CEST 2009
No there is no publication on these or related methods. But have you read
Section 10.3 "Testing across contrasts" in the limma User's Guide which
discusses these methods? You might also find it helpful though to search
for my replies to previous questions about decideTests on this mailing
I recommend "global" whenever you have a series of contrasts that you are
analysing together, especially if you want to compare the number of DE
genes that you find. There is no requirement that the contrasts be of
similar "strength". An advantage of "global" is that the same t-statistic
cutoff is used for all contrasts (in the absence of weights or NAs).
However you need to be aware that the number of DE genes for any contrast
will depend on what other contrasts it is tested with -- contrasts with
lots of DE genes will pull the others up.
I recommend "separate" if you are analysing different contrasts for
different purposes, so the numbers of DE genes are not comparable.
"nestedF" has a specialist purpose in trying to give more weight to genes
which are simultaneously DE in two or more several contrasts. Both this
and "hierarchical" are somewhat experimental in that I have not published
the theory, and therefore I don't strongly recommend them.
> From: Michal Kol?? <kolarmi at img.cas.cz>
> Subject: [BioC] Methods in decideTests (limma)
> To: bioconductor at stat.math.ethz.ch
> Message-ID: <62C854CA-B73C-4B73-A383-51ED398CCCE3 at img.cas.cz>
> Content-Type: text/plain; charset=UTF-8; delsp=yes; format=flowed
> Dear list,
> I would like to ask on the theory behind various methods in
> decideTests. The method "separate" is clear to me, giving p-value
> adjustment for each contrast separately. The method "global" may be
> used presumably when there are two or more contrasts of similar
> strength in the experiment. The method "nestedF" seems to me similar
> to the "global", yet it considers for p-value adjustment only those
> genes for which F-test is significant after p-value correction
> (roughly said). Is that correct? And finally, the method
> "hierarchical" considers for the final p-value adjustment only those
> genes/contrasts for which adjusted p-value (of the gene in the
> contrast treated separately) is smaller than some cut-off. Is that
> My next question is whether any of the methods "global",
> "hierarchical" or "nestedF" can be used to correct p-values for
> contrasts that have different strength (different number of expected
> DEGs)? In my case 'different' means hundreds of DEGs for one contrast
> and tens for the other.
> Can I find more details on the methods in some reference?
> Michal Kol??
> Academy of Sciences of the Czech Republic
> Institute of Molecular Genetics
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