[BioC] Limma final gene expression report

[Gordon K Smyth]

> Date: Mon, 9 May 2005 22:15:17 -0700 (PDT)
> From: Ankit Pal <pal_ankit2000 at yahoo.com>
> Subject: [BioC] Limma final gene expression report
> To: bioconductor at stat.math.ethz.ch
>
> Dear All,
> While looking at the Limma user guide, I came across
> the following example
>
>> targets <- readTargets("SwirlSample.txt")
>> RG <- read.maimages(targets$FileName, source="spot")
>
>> RG$genes <- readGAL()
>> RG$printer <- getLayout(RG$genes)
>> MA <- normalizeWithinArrays(RG)
>> MA <- normalizeBetweenArrays(MA)
>> fit <- lmFit(MA, design=c(-1,1,-1,1))
>> fit <- eBayes(fit)
>> options(digits=3)
>> topTable(fit, n=30, adjust="fdr")
> ID        Name       M    A     t  P.Value    B
> control   BMP2      -2.21 12.1 -21.1 0.000357 7.96
> control   BMP2      -2.30 13.1 -20.3 0.000357 7.78
> control   Dlx3      -2.18 13.3 -20.0 0.000357 7.71
> control   Dlx3      -2.18 13.5 -19.6 0.000357 7.62
> fb94h06 20-L12       1.27 12.0  14.1 0.002067 5.78
> fb40h07  7-D14       1.35 13.8  13.5 0.002067 5.54
>
> I have omitted a few rows and columns.
> Here we see that after all the data transformations,
> we get an output where the ranking for the probes in
> an array is  done on the basis of the B value.
> Notice that there are reapeating names for genes,
> therefore for a set of replicates, within and across
> arrays, each spot is reported separately as an
> individual entity.
> In the case of BMP2 from the above example, which
> result do I consider?
> Is there a way in which I can get a single result for
> a set of replicates.

No, there isn't.  The limma facility to handle duplicate spots applies only when every single
probe on your array is replicated the same number of times in a regular pattern.  (The intention
is to accommodate repeating printing from the same DNA wells, not irregularly repeated occurance
of similar DNA in different wells of the DNA plates.)  For the Swirl dataset which you're using
here, the only probes which are repeated are control probes.  There seems to me to be no purpose
in averaging results for repeated control probes because then they would be treated differently
from library probes and hence would no longer be comparable to the library probes in the
statistical analysis.  Similar treatment is necessary for them to be truly control probes.  The
fact that you get both copies of the BMP2 control probe at the top in the above list is useful
information -- it shows that the top ranking is no fluke.

Gordon

> I am new to this package, so please do let me know if
> there is a problem in my understanding the concept.
> Thank you,
> -Ankit