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! Sherosha > > ---------- 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 > > >