[BioC] limma design matrix

[Shi, Tao]

Is there a way to extract the original (without moderating the residual mean squares) F stat or F.p.value before apply eBayes step?  I know I can do this by writing a function and apply it to each gene, but lmFit is much faster....

...Tao

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Message: 11
Date: Tue, 11 Jan 2005 17:46:40 +1100
From: Gordon Smyth 
Subject: [BioC] limma design matrix
To: "Auer Michael"michael.auer at meduniwien.ac.at
Cc: bioconductor at stat.math.ethz.ch
Message-ID: <6.2.0.14.1.20050111174221.0215e5d0 at imaphost.wehi.edu.au>
Content-Type: text/plain; charset="us-ascii"; format=flowed

See limma User's Guide http://bioinf.wehi.edu.au/limma/usersguide.pdf 
middle of page 32.

Gordon

Mon Jan 10 17:42:20 CET 2005
>Hi
>
>I know this has been dealt with before, but I would really appreciate some
>help.
>I am anaylsing affy chips and I have three different sample types,
>lpl-high, lpl-low and brain.
>I construct a factor vector below
>TS <-c(rep("lpl-high",12),rep("lpl-low",10),rep("brain",17))
>TS<- factor(TS, levels= c("lpl-high","lpl-low","brain"))
>
>I would simply want to make an analysis of variance, see wheter these
>three samples are differentially expressed (F value). I am not interested
>in any contrasts. How can I do that?
>
>Thanks a lot!!!!!






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