[BioC] LIMMA : design (1, 2, 3, 3 ) , I got EXCITING results, what could be the logic, since i have 2 replicates for 3rd group only ?

[Naomi Altman]

Significance should be based on biological replication.  If the 2 chips for 
group 3 are technical replicates, then the variance estimate for the test 
is probably too small.

In theory, statistical tests need only 2 replicate in a single condition, 
as the null distribution accounts for the number of replicates.   However, 
for this theory to hold, the normality of the samples must be pretty 
good.  When the data are exactly normally distributed (and the assumptions 
for limma for the distribution of variance hold) then the FDR values should 
be pretty good, but the FNR will be poor (as you have no power).

However, I don't think anyone believes that microarray data are normally 
distributed.  So, I would not really trust these results, even if you have 
a biological replicate.  Of course the 2-fold rule is even worse, so really 
you should do more biological replication.

--Naomi

At 09:51 PM 4/26/2005, Saurin Jani wrote:
>Hi Adai,
>
>Yes, you are right. I have 4 samples :
>
>Group1 = Growth Effect for Day 1 : 1 Affy GeneChip.
>Group2 = Growth Effect for Day 2 : 1 Affy GeneChip.
>Group3 = Growth Effect for Day 3 : 2 Affy GeneChips.
>
>so, my design matrix is:
>design <- model.matrix(~ -1+factor(c(1,2,3,3)));
>
>LIMMA did not give any error or waring even it has 1
>sample per group...! ( I thought similar thing,  since
>it needs technical replicates per group to make a
>decision). The results are very interesting. I have
>many genes for 0.01 FDR, which is very good.
>
>Somehow,I don't understand the logic. Do you think is
>this a valid design? Or You think I should go by Fold
>Change Logic. Please, let me know.
>
>Thank you very much,
>Saurin
>
>
>
>
>
>--- Adaikalavan Ramasamy <ramasamy at cancer.org.uk>
>wrote:
> > PLEASE correct me if I am wrong.
> >
> > You have a total of 4 samples that could be
> > classified into one of 3
> > groups ? How do you plan on distinguishing
> > biological from technical
> > variation ? Shouldn't limma come with some sort of
> > warning or error if
> > there are only one sample per group ?
> >
> > Regards, Adai
> >
> >
> >
> > On Tue, 2005-04-26 at 10:01 -0700, Saurin Jani
> > wrote:
> > > Hi BioC,
> > >
> > > I have 3 groups but I have only 2 replicates for
> > last
> > > group. so, group 1 and 2 has only one Affy CEL
> > file. I
> > > Did..LIMMA as below and I got some Exciting
> > results:
> > >
> > > #----------------------------------
> > > design <- model.matrix(~ -1+factor(c(1,2,3,3)));
> > > colnames(design) <-  c("g1","g2","g3");
> > > fit <- lmFit(myRMA,design);
> > >
> > > contrast.matrix <-
> > > makeContrasts(g1-g2,g1-g3,g2-g3,levels = design);
> > >
> > > fit2 <- contrasts.fit(fit,contrast.matrix);
> > > fit2 <- eBayes(fit2);
> > >
> > > results <-
> > > decideTests(fit2,adjust="fdr",p.value=0.01);
> > >
> > > myGenes <- geneNames(myRMA);
> > > i <- apply(results,c(1,2),all);
> > >
> > > a <- i[,1];
> > > b <- i[,2];
> > > c <- i[,3];
> > > tempgenes1 <- myGenes[a];
> > > tempgenes2 <- myGenes[b];
> > > tempgenes3 <- myGenes[c];
> > >
> > > tempall <- c(tempgenes1,tempgenes2,tempgenes3);
> > > myDEGenes <- tempall;
> > >
> > > esetSub2X <- MatrixRMA[myDEGenes,];
> > > esetSub2 <- new("exprSet",exprs = esetSub2X);
> > > pData(esetSub2) <- pData(myRMA);
> > > heatmap(esetSub2X);
> > > #----------------------------------
> > >
> > > I got EXCITING results, what could be the
> > logic,since
> > > i have 2 replicates for 3rd group only ?
> > >
> > > Could anyone point me out ?
> > >
> > > I highly appreciate your help , Thank you in
> > advance.
> > >
> > > Thank you,
> > > Saurin
> > >
> > > _______________________________________________
> > > Bioconductor mailing list
> > > Bioconductor at stat.math.ethz.ch
> > > https://stat.ethz.ch/mailman/listinfo/bioconductor
> > >
> >
> >
>
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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