How to avoid losing a sample as reference running an individual differential expression analysis (LIMMA)
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@gordon-smyth
Last seen 2 hours ago
WEHI, Melbourne, Australia
> Date: Tue, 10 Feb 2009 06:04:23 -0800 (PST) > From: Dmitriy Verkhoturov <verkhoturovdm at="" yahoo.com=""> > Subject: [BioC] How to avoid losing a sample as reference running an > individual differential expression analysis (LIMMA) > To: bioconductor at stat.math.ethz.ch > > Hello listmemebers, > > > I have data from two-color microarray expression profiling experiments > where 3 whole brain (WB) samples were compared to 3 Mauthner Cells (MC) > in a loop design (-> MC #1 -> WB #1 -> MC #2 -> WB #2 -> MC #3 -> WB #3 > -> MC #1 ->). In addition to phenotype analysis I would also like to run > an individual analysis making all pair-wise comparisons. I'm using the > LIMMA package in R to do this. The problem is that the contrast matrix > that you have to set up requires that one of the samples be designated > as a reference, but in doing so you lose the sample. No you do not lose the reference sample in any way. On the contrary, comparisons are automatically computed between the nominal reference and all the other treatments. Please read the documentation a little more carefully. Best wishes Gordon > My question is this, is it possible to run individual analysis with this > data set without losing one as a reference point? > > Many thanks in advance, > Dmitriy
Microarray limma BRAIN Microarray limma BRAIN • 923 views
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