Hi,

Did you get chance to look at: "Effects of filtering by Present call on
analysis of microarray experiments" by McClintick JN, Edenberg HJ, BMC
Bioinformatics 2006, 7:49 (31 January 2006) ?

Hope, this helps !
Sharon

On 10/26/06, Kimpel, Mark William <mkimpel@iupui.edu> wrote:
>
> Jenny and Naomi,
>
> Thank you for your replies and code (Jenny). I did not mean to imply
> that I would throw out probesets if they are present in only one
> phenotype, but that I would keep in probesets if the same actual number
> were counted present across all samples.
>
> Say, for example, we have 10 samples with 5 in each phenotype. We decide
> that we would like to pass through our filter any probeset that is
> present in at least 80% of probesets (4) within a phenotype. I would
> argue that to absolutely reduce bias we should construct the filter so
> that we pass through probesets that are present in 4 out of 10 samples.
>
> This is actually a more generous filter but would seem to better
> preserve the underlying statistical distribution of data, which the BH
> FDR method depends on.
>
> I do recognize that, by passing a few more genes through the filter,
> that we will end up raising the calculated FDR of all probesets tested
> and that, thereby, we may end up with fewer significant probesets. But,
> would we have more confidence in those?
>
> I also recognize that these effects will be subtle and perhaps have
> little practical effect, but I do want to be rigorous in my approach.
>
> Your responses?
>
> Thanks,
>
> Mark
>
> Mark W. Kimpel MD
>
>
>
> (317) 490-5129 Work, & Mobile
>
>
>
> (317) 663-0513 Home (no voice mail please)
>
> 1-(317)-536-2730 FAX
>
>
> -----Original Message-----
> From: bioconductor-bounces@stat.math.ethz.ch
> [mailto:bioconductor-bounces@stat.math.ethz.ch] On Behalf Of Jenny
> Drnevich
> Sent: Thursday, October 26, 2006 10:42 AM
> To: bioconductor@stat.math.ethz.ch
> Subject: Re: [BioC] advice on absent present filtering needed
>
> I concur - You do not want to throw out genes that only express in one
> phenotype. If you plot a histogram of the number of present calls for
> each
> gene, you will see that the vast majority of genes are either present in
>
> all samples or absent in all samples. It is only the small number of
> genes
> in between that your filter options will affect. To be conservative, I
> keep
> a gene even if it is present in only 1 sample, so I don't even consider
> phenotype. The difference really will only affect a few hundred genes,
> which won't matter too much in terms of fdr correction, so I say be
> conservative so you don't throw out a gene that is expressed in only one
>
> phenotype. To check the histogram:
>
> calls.eset <- mas5calls(abatch)
>
> hist(apply(exprs(calls.eset), 1, function(x)  sum(x=="P")))
>
> Cheers,
> Jenny
>
> At 08:27 AM 10/26/2006, you wrote:
> >Your colleague is right.  Surely it is important to know if some
> >genes express only in certain phenotypes.  Your method loses this
> information.
> >
> >--Naomi
> >
> >
> >At 10:53 PM 10/25/2006, Kimpel, Mark William wrote:
> > >I have a question about how to properly apply the MAS5 absent
> > >present filtering technique. Within my group, I am advocating
> > >setting a cutoff ratio of absent present across phenotypes (i.e. all
> > >samples), whereas a colleague is advocating applying the filter
> > >within phenotype and passing through the filter any probeset with
> > >the A/P ratio of >0.5 within any of the phenotypes (we have 3).
> > >
> > >The argument my colleague makes is that some probesets may only be
> > >expressed by one phenotype and we want to keep these in, but be
> > >stringent within phenotype. This makes some biologic sense, but I am
> > >concerned that this filtering within phenotype will introduce bias
> > >as low expression levels, as it would seem to, at least in some
> > >cases, act like a fold filter at expression levels near the limit of
> > >reliable detection.
> > >
> > >Advice?
> > >
> > >Mark
> > >
> > >Mark W. Kimpel MD
> > >
> > >
> > >Official Business Address:
> > >
> > >Department of Psychiatry
> > >Indiana University School of Medicine
> > >PR M116
> > >Institute of Psychiatric Research
> > >791 Union Drive
> > >Indianapolis, IN 46202
> > >
> > >Preferred Mailing Address:
> > >
> > >15032 Hunter Court
> > >Westfield, IN  46074
> > >
> > >(317) 490-5129 Work, & Mobile
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> > >(317) 663-0513 Home (no voice mail please)
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> > >
> > >_______________________________________________
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> >
> >Naomi S. Altman                                814-865-3791 (voice)
> >Associate Professor
> >Dept. of Statistics                              814-863-7114 (fax)
> >Penn State University                         814-865-1348 (Statistics)
> >University Park, PA 16802-2111
> >
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>
> Jenny Drnevich, Ph.D.
>
> Functional Genomics Bioinformatics Specialist
> W.M. Keck Center for Comparative and Functional Genomics
> Roy J. Carver Biotechnology Center
> University of Illinois, Urbana-Champaign
>
> 330 ERML
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> e-mail: drnevich@uiuc.edu
>
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