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List:       bioconductor
Subject:    Re: [BioC] Limma lmFit function and spot quality weights
From:       Benoit <benoit.loup () jouy ! inra ! fr>
Date:       2009-07-31 8:03:45
Message-ID: 4A72A561.70002 () jouy ! inra ! fr
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Dear Gordon,

Thank you for your answer.
I understand the interest to make comparisons even with one sample per 
group, it could be informative but in my analysis I try to identify 
robust differential expressed genes.
Concerning the weights, I am a very new user in R and Limma and it's not 
easy to generate appropriate weights. Curently, I'm using 0 and 1 flags. 
I know that it's possible to use intermediate weight values but I don't 
know on which probe allocate these values.
Another question is, is it judicious to filter before or after fitting 
linear model ?
On affy data, I apply filtering on the PMA call before analysing with 
limma and keep probe with only a minimal number of "P" calls per group. 
Do you think it is pertinent or is it a bad method ?

Thanks,

Benoit

Gordon K Smyth a écrit :
> Dear Benoit,
> 
> It doesn't seem to me to be desirable to place restrictions on the 
> weights that people can specify to lmFit. In some cases it is 
> desirable to be able to make comparisons for probes with only one 
> available sample per group.
> 
> On the other hand, this does means that you are responsible for the 
> weights you create, and you may get poor results if you input weights 
> that are innappropriate for the data.
> 
> Best wishes
> Gordon
> 
> > Date: Mon, 27 Jul 2009 13:41:06 +0200
> > From: Benoit <benoit.loup@jouy.inra.fr>
> > Subject: [BioC] Limma lmFit function and spot quality weights
> > To: bioconductor@stat.math.ethz.ch
> > 
> > Hello,
> > I'm using Limma to assess differential expression on double colour
> > microarray data and have a question about the lmFit function.
> > When I fit linear model using lmFit, as I understood, the function uses
> > the weights extracted from the MA object when present and/or specified.
> > Thus, I tried fitting with and without the spot quality weights and I
> > found different results (not very surprising in fact).
> > In fact, when I used weights, zero weighted spots seemed to be removed
> > from the analysis and it's here that I have a problem.
> > 
> > For my experiment, I compare two groups (control vs treated) in a
> > classical design experiment "Two Groups: Common Reference" as describe
> > in the Limma documentation.
> > 
> > design=modelMatrix(targets,ref="ref")
> > design
> > fit=lmFit(MA,design,weights=MA$weights)
> > /alternative without weights : fit=lmFit(MA,design,weights=NULL)/
> > cont.matrix=makeContrasts(pollutedVScontrol=polluted-control,polluted,control,levels=design) \
> >  
> > cont.matrix
> > fit2=contrasts.fit(fit,cont.matrix)
> > fit2=eBayes(fit2)
> > res=toptable(coef=1,number=15744,fit=fit2,genelist=fit2$genes,adjust.method="BH",A=fit2$Amean,eb=fit2,p.value=0.01) \
> >  
> > 
> > The difference between the analysis with and without weights is that
> > when I use weights new genes highly differentially expressed appeared.
> > When I control these genes, in fact they correspond to spots that are
> > flagged (0) on the majority of the arrays (i.e. only one weight at 1 for
> > the control and one weight at 1 for the treated). Thus for these genes
> > the comparison is performed only one "control array" versus one "treated
> > array".
> > So is it possible to specify to lmFit that there must be a minimum of
> > "1" weights or a maximum "0" weights per groups of array ?
> > 
> > Thank you for any help you can bring me.
> > 
> > Benoit
> > 
> > -- 
> > Benoit Loup, PhD
> > UMR Biologie du D?veloppement et Reproduction
> > Diff?renciation des Gonades et Perturbations
> > INRA ? Domaine de Vilvert
> > B?timent Jacques Poly
> > 78350 Jouy en Josas
> > France
> > 
> > Tel: 33 1 34 65 25 38
> > Fax: 33 1 34 65 22 41
> > E-mail: benoit.loup@jouy.inra.fr
> 
> 

-- 
Benoit Loup, PhD
UMR Biologie du Développement et Reproduction
Différenciation des Gonades et Perturbations
INRA – Domaine de Vilvert
Bâtiment Jacques Poly
78350 Jouy en Josas
France

Tel: 33 1 34 65 25 38
Fax: 33 1 34 65 22 41
E-mail: benoit.loup@jouy.inra.fr

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