[BioC] Filtering before differential expression analysis of microarrays - New paper out (James W. MacDonald)
sherosha at gmail.com
Tue Jan 13 19:09:29 CET 2009
This is how I setup the filters:
Around here I sub-select the probesets that come through the filter
from my expression set.
then proceed to
> fit=lmFit(all.esetsub[,61:102],design) #from a large eset normalised over 102 chips so subsetting the relevant cel files
If I were to filter here using the two filters above......
#When I filter before starting limma, I get 11504 probesets coming through.
#I am confused how to proceed with the next steps....(i.e subset the
fit2 object and apply the eBayes)..:-(
#previously proceeded as follows after the "contrasts.fit" step:
I have been previously using filters before limma, but I 've been
following the discussions on this board and would try to see how the
data looks if I filtered prior o the eBayes step.
Any help is greatly appreciated!!
Thank you very much!
2009/1/13 Jenny Drnevich <drnevich at illinois.edu>:
> Hi Sherosha,
> In general, you can filter by subsetting a MArrayLM object the exact same
> way as you would an ExpressionSet object. If you have any trouble, please
> post the code that you are trying to use.
> At 10:47 AM 1/13/2009, Sherosha Raj wrote:
>> Hello all
>> I"m sorry if this is a simple question, but how does one go about
>> filtering after the eBayes step since the resulting object is of the
>> class MArrayLM?
>> I am used to filtering expression sets directly.
>> Thank you very much!
>> > ---------- Forwarded message ----------
>> > From: "James W. MacDonald" <jmacdon at med.umich.edu>
>> > To: Daniel Brewer <daniel.brewer at icr.ac.uk>
>> > Date: Mon, 12 Jan 2009 09:25:02 -0500
>> > Subject: Re: [BioC] Filtering before differential expression analysis of
>> > microarrays - New paper out
>> > Hi Dan,
>> > Daniel Brewer wrote:
>> >> Hi,
>> >> There is a new paper out at BMC bioinformatics that seems to justify
>> >> the
>> >> use of filtering before differential expression analysis is performed
>> >> (Hackstadt & Hess BMC Bioinformatics 2009, 10:11 -
>> >> http://www.biomedcentral.com/1471-2105/10/11/abstract). Specifically
>> >> filtering by variance and detection call. I have got the impression
>> >> from this list that the general opinion is that one should only filter
>> >> out the control genes before testing. I was wondering if anyone had
>> >> any
>> >> opinions on this paper and the topic in general.
>> > I'm sure people do have opinions about this topic ;-D
>> > The reason people have so many opinions is because it isn't a simple
>> > question, and it depends on what you consider important.
>> > If you are just trying to limit the number of multiple comparisons to
>> > increase power, then filtering first is probably the way to go.
>> > If you are concerned with the accuracy of the FDR estimates, then
>> > filtering first may not be ideal.
>> > If you are using limma (Hackstadt and Hess used multtest), then you
>> > should filter after the eBayes step but before the FDR step, as an
>> > assumption of the eBayes step is that all of the data from the chip are
>> > available.
>> > Unless of course you are concerned about the accuracy of the FDR
>> > estimates, in which case... well you see the point.
>> > With microarray data analysis the arguments for and against a particular
>> > way of doing things can shed more heat than light, as nobody really knows
>> > the underlying truth, and the measures we use are really far removed from
>> > the actual phenomenon we are testing.
>> > Best,
>> > Jim
>> >> Many thanks
>> >> Dan
>> > --
>> > James W. MacDonald, M.S.
>> > Biostatistician
>> > Hildebrandt Lab
>> > 8220D MSRB III
>> > 1150 W. Medical Center Drive
>> > Ann Arbor MI 48109-5646
>> > 734-936-8662
>> Bioconductor mailing list
>> Bioconductor at stat.math.ethz.ch
>> Search the archives:
> 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
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