[BioC] limma lmFit error: Coefficients not estimable

[Gordon K Smyth]

Dear Maxim,

Thanks for the code example.  Your design matrix really is singular, as 
can easily be confirmed in a variety of ways.  This is not a bug in limma.

Also this not an "error".  It is a perfectly helpful diagnostic message 
that the software is giving you.

Best wishes
Gordon

> Date: Wed, 17 Mar 2010 16:11:10 +0000
> From: "Freydin, Maxim" <m.freidin at imperial.ac.uk>
> To: "'bioconductor at stat.math.ethz.ch'"
> 	<bioconductor at stat.math.ethz.ch>
> Subject: [BioC] limma lmFit error: Coefficients not estimable
> Message-ID:
>
> Hello,
>
> I found that the question was already answered, but the solution proposed did not work for me.
>
> Could you please help to resolve an issue with limma I faced. Please see the attachment. I have a set of arrays for 4 groups of patients (Atype) taken at two time points (Visit). Every patient was analyzed twice, so they are paired and I cannot ignore this. The questions are 1) what genes are differentially expressed between time points in every group; 2) what genes are differentially expressed between disease types at V1 and V3.
> I make a design matrix this way:
>
> atype<-factor(c("lco","bri","bri","bri","con","con","con","lco","mild","mild","mild","lco","con","con","lco","bri","bri","bri","con","con","con","lco","mild","mild","mild","lco","con","con"))
> patient<-factor(c("x1","x8","x10","x14","x17","x18","x19","x20","x24","x26","x27","x29","x31","x38","x1","x8","x10","x14","x17","x18","x19","x20","x24","x26","x27","x29","x31","x38"))
> visit<-factor(c("v1","v1","v1","v1","v1","v1","v1","v1","v1","v1","v1","v1","v1","v1","v3","v3","v3","v3","v3","v3","v3","v3","v3","v3","v3","v3","v3","v3"))
> fact<-paste(visit,atype,sep=".")
> fact<-as.factor(fact)
> design<-model.matrix(~0+fact+patient)
> colnames(design)<-c(levels(fact),colnames(design[,9:21]))
>
> cont<-makeContrasts(Mild.Bri.V1=v1.mild-v1.bri,Mild.Bri.V3=v3.mild-v3.bri,Mild.Bri.V1.V3=(v1.mild-v3.mild)-(v1.bri-v3.bri),Mild.Con.V1=v1.mild-v1.con,Mild.Con.V3=v3.mild-v3.con,Mild.Con.V1.V3=(v1.mild-v3.mild)-(v1.con-v3.con),Mild.Lco.V1=v1.mild-v1.lco,Mild.Lco.V3=v3.mild-v3.lco,Mild.Lco.V1.V3=(v1.mild-v3.mild)-(v1.lco-v3.lco),Bri.Con.V1=v1.bri-v1.con,Bri.Con.V3=v3.bri-v3.con,Bri.Con.V1.V3=(v1.bri-v3.bri)-(v1.con-v3.con),Bri.Lco.V1=v1.bri-v1.lco,Bri.Lco.V3=v3.bri-v3.lco,Bri.Lco.V1.V3=(v1.bri-v3.bri)-(v1.lco-v3.lco),Lco.Con.V1=v1.lco-v1.con,Lco.Con.V3=v3.lco-v3.con,Lco.Con.V1.V3=(v1.lco-v3.lco)-(v1.con-v3.con),levels=(design))
>
> fit<-lmFit(eset.norm,design)
>  # Coefficients not estimable: patientx27 patientx38 patientx8
>
> fit2<-eBayes(contrasts.fit(fit,cont))
>
>
> In my opinion, the design matrix looks all right, so does it mean there is a bug in limma?
> Thanks
>
> Best wishes,
> Maxim

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