[BioC] nested design with random factor and limma???
Gordon K Smyth
smyth at wehi.EDU.AU
Sun Jul 20 03:40:19 CEST 2008
limma handles random factors using the duplicateCorrelation() function --
see the User's Guide Section 8.2 for an example. It is admitedly an
unusual method, but quite effective.
> Date: Mon, 14 Jul 2008 11:25:00 +0200
> From: Bettina Kulle Andreassen <b.k.andreassen at medisin.uio.no>
> Subject: [BioC] nested design with random factor and limma???
> To: bioconductor at stat.math.ethz.ch
> Message-ID: <487B1B6C.3050504 at medisin.uio.no>
> Content-Type: text/plain; charset=ISO-8859-1; format=flowed
> i have the following dataset:
> - 26 indivuals with expressiondata (log-ratio from common ref design)
> (random factor: patient)
> - each individual has expression data from 1 to 3 different (but fixed)
> locations (fixed factor: location)
> - 14 controls, 12 patients (fixed factor: group)
> i am mainly interested in the group effect!
> i tried limma, but it did not seem to work with my random
> factor patient?.
> any suggestions?
> thanks for help!
> Bettina Kulle Andreassen
> Associate Professor
> University of Oslo
> Faculty Division Ahus
> Institute for clinical epidemiology
> and molecular biology (Epi-Gen)
> Sykehusveien 27
> N-1474 Nordbyhagen
> tel: +47 67927762
> fax: +47 67927803
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