[BioC] limma

Gordon K Smyth smyth at wehi.EDU.AU
Wed May 4 14:41:04 CEST 2005


> Date: Mon, 02 May 2005 23:11:57 +0100
> From: "Anita Grigoriadis" <Anita.Grigoriadis at icr.ac.uk>
> Subject: [BioC] limma
> To: <bioconductor at stat.math.ethz.ch>
>
> Hi, I am using limma to identify differentially expressed genes on 4
> different platforms (CodeLink, Affymetrix, Agilent and an inhouse cDNA
> array), 2 RNA samples, 3 replicates for each on the one color
> microarrays, 6 replicates for the two color arrays.   I used limma with
> fdr to adjust the p-value, and my result of differential genes from
> Affymetrix to the inhouse cDNA array was from 8000 to 500 differentially
> expressed probe sets.

The number of genes coming up will depend on the precision of the platform, the number of
replicates, the design of the experiment and the number of probes, so it is not surprising that
the number of genes above a significance threshold will vary from one platform to another.

> My  question: is it reasonable to apply the same

The same significance threshold?  I guess it is if you're trying to identify differentially
expressed probes.  If your real purpose is to compare the platforms, this isn't the way I'd go
about it.

Gordon

> Thanks for some advice
> Anita
>
>
> Dr Anita Grigoriadis
> The Breakthrough Toby Robins
> Breast Cancer Research Centre,
> Institute of Cancer Research,
> 237 Fulham Road,
> London, SW3 6JB



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