Entering edit mode
> Date: Wed, 30 Jul 2014 22:01:34 +0000
> From: "Rao,Xiayu" <xrao at="" mdanderson.org="">
> To: "bioconductor at r-project.org" <bioconductor at="" r-project.org="">
> Subject: [BioC] multi-level design - a simplified question -
corrected
> table
>
> Hello all,
>
> I do need some help on analyzing such unorganized data. Please help
me out. Thank you so much!
> I basically followed the analysis of multi-level experiments in
limma user guide. But I do not feel right about the code below. Please
give me some suggestions.
>
> # I want to compare Normal vs. Tumor negative, and Normal vs Tumor
positive. There are partial pairing (subject) and batch effect (chip).
> Treat <- factor(paste(targets$chip,targets$type,sep="."))
> design <- model.matrix(~0+Treat)
No, this isn't correct. If you need to correct for a batch effect
(and
have you checked that you really need this?), then it should be
design <- model.matrix(+0+type+chip)
where type and chip are both factors. Then, when you take contrasts
later
on, you simply compare the type levels that are relevant.
Or better still,
type <- relevel(type, ref="N")
design <- model.matrix(~type+chip)
corfit <- duplicateCorrelation(y,design,block=targets$subject)
fit <-
lmFit(y,design,block=targets$subject,correlation=corfit$consensus)
fit <- eBayes(fit)
topTable(fit, coef="typeTneg")
topTable(fit, coef="typeTpos")
Best wishes
Gordon
> colnames(design) <- levels(Treat)
>
> corfit <- duplicateCorrelation(y,design,block=targets$subject)
> corfit$consensus
> fit <-
lmFit(y,design,block=targets$subject,correlation=corfit$consensus)
> cm <-
makeContrasts(TposvsN=(a1.Tpos+a2.Tpos+a3.Tpos)/3-(a1.N+a2.N)/2,
TnegvsN=(a1.Tneg+a3.Tneg)/2-(a1.N+a2.N)/2, levels=design) ????
> fit2 <- contrasts.fit(fit, cm)
> fit2 <- eBayes(fit2)
> topTable(fit2, coef=1, sort.by="p")
>
> sample type subject chip
> s1 Tneg 1 a1
> s2 N 1 a1
> s3 Tpos 2 a1
> s4 N 2 a1
> s5 Tneg 3 a1
> s6 N 3 a1
> s7 Tpos 4 a1
> s8 N 4 a1
> s9 Tpos 5 a2
> s10 N 5 a2
> s11 N 6 a2
> s12 Tpos 7 a2
> s13 N 7 a2
> s14 Tpos 8 a2
> s15 N 8 a2
> s16 Tneg 9 a3
> s17 Tneg 10 a3
> s18 Tneg 11 a3
> s19 Tpos 6 a3
> s20 Tpos 12 a3
> s21 Tneg 13 a3
> s22 Tpos 14 a3
>
>
> Thanks,
> Xiayu
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