[BioC] questions on results from mt.maxT (multtest)

[Adaikalavan Ramasamy]

Well spotted. So I guess the authors of mt.maxT() were clever enough to
note that complete enumeration is possible for small number of
iterations and wrote an overriding condition (using mt.getmaxB) as not
waste time with 10000 iteration.ns.

I guess another way of looking at your problem is that 3 vs. 3 is does
not have sufficient power to detect with this correction and the
obtained p-values reflect this.

One possibility is to use the normal t-test or wilcoxon to obtain a
vector of p-values and then adjust it for multiple testing. However
since I am no expert in multiple hypothesis testing, I hope someone else
can answer your question. Sorry.

Regards, Adai



On Mon, 2005-02-14 at 11:25 -0500, Straubhaar, Juerg wrote:
> Hi Adai,
> 
> The multtest version I am using is version 1.5.2 and the default value of B is 10000. Even if I set B to 100000 only 20 permutations will be calculated. I have two classes and 3 members in each class. The maximum number of permutations of the 6 columns (2 X 3) is 20. So how can I do 10000 permutations?
> 
> Juerg
> 
> 
> -----Original Message-----
> From: Adaikalavan Ramasamy [mailto:ramasamy at cancer.org.uk]
> Sent: Sun 2/13/2005 10:45 PM
> To: Straubhaar, Juerg
> Cc: BioConductor mailing list
> Subject: Re: [BioC] questions on results from mt.maxT (multtest)
>  
> The resolution of your p-value by permutation test is 1/B where B is the
> number of iterations. In the output shows, I think it says B=20. Thus
> your resolution (or smallest p-value) is 1/20 = 0.05.
> 
> However I am wondering why did your function mt.maxT() default to B=20
> when the current of multtest (1.5.2) has a default of B=10000 ?
> 
> Are you by any chance using a very old version of multtest ? If so, you
> can try upgrading or explicitly set B=10000 (or something higher) in
> mt.maxT. Otherwise check your inputs.
> 
> Regards, Adai
> 
> 
> On Sun, 2005-02-13 at 13:02 -0500, Straubhaar, Juerg wrote:
> > Im am using R version 2.0.1, multtest version 1.5.2.
> > 
> > Microarray experiment: wildtype tissue vs KO tissue; affy MOE430_2
> > Experiments in triplicates.
> > 
> > ExprSet at exprs matrix has dimension: 45101 6
> > 
> > I used nonspecific filtering which reduces the number of genes to 1815 (exprSub)
> > 
> > I am using multtest to get a set of differentially expressed genes:
> > 
> > resT <-mt.maxT(exprSub at exprs, c(0,1,0,1,0))
> > This runs 20 permutations (complete enumeration)
> > 
> > sort(resT$rawp) looks like this:
> > 
> > [1] 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
> > [20] 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
> > [39] 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
> > ...
> > [1711] 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9
> > [1729] 0.9 0.9 0.9 0.9 0.9 0.9 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
> > [1747] 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
> > [1765] 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
> > [1783] 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
> > [1801] 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0
> > 
> > It looks like these p-values are rounded to one decimal digit. From these results none of the 1815  genes are differentially expressed between WT and KO, which is not quite believable. I would like to get p-values precise to several digits. Maybe there is something else I don't understand.
> > 
> > getOption('digits') 7
> > 
> > Thank you.
> > 
> > Juerg Straubhaar
> > Umass Med
> > 
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> > Bioconductor at stat.math.ethz.ch
> > https://stat.ethz.ch/mailman/listinfo/bioconductor
> > 
> 
>