[BioC] limma design matrix

[Naomi Altman]

Create the contrasts. Use limma and FStat on the results.

Or, to do a classical ANOVA, use apply to do an aov to each gene and use 
anova to get the F-stat from the aov output.

e.g. myanova=function(x,y){
#x=expression for 1 gene
#y=TS
anova(aov(x~-1+y))
}

ANOVAlist=apply(exprsmat,1,myanova,y=TS)

Each component of ANOVAlist is the ANOVA table for 1 row of exprsmat.

At 05:42 PM 1/10/2005 +0100, Auer Michael wrote:

>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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Naomi S. Altman                                814-865-3791 (voice)
Associate Professor
Bioinformatics Consulting Center
Dept. of Statistics                              814-863-7114 (fax)
Penn State University                         814-865-1348 (Statistics)
University Park, PA 16802-2111