[BioC] basic limma questions
Endre Sebestyen
endre.sebestyen at gmail.com
Mon Mar 31 13:32:32 CEST 2008
Thanks for your answer. A little more details :
I had a control and a treatment, with 3 technical replicates and no
dye-swaps. Cy3 was the treated, Cy5 the untreated.
The ArrayVision result file looks like this :
Ctrl Ctrl Ctrl Data Data
Data
Spot labels VOL - MDC Bkgd sVOL VOL - MDC Bkgd
sVOL Ratio (sVOL): Data / Ctrl Diff (sVOL): Data - Ctrl
MZ00023554 - TC248295 (1) 87573.5998 29969.817
57603.783 51217.7619 15349.622 35868.140 0.623
-21735.643
MZ00023408 - TC248006 (1) 29389.2252 29831.153 0.000
15896.2700 15349.622 546.648 1.0000e+100 546.648
I extracted the ID, Ctrl VOL, Ctrl Bkgd, Data VOL, Data Bkgd columns.
When I used the read.maimages function, Ctrl VOL became R, Data VOL
became G, Ctrl Bkgd became Rb, DataBkgd became Gb.
Endre
On Mon, Mar 31, 2008 at 5:36 AM, Gordon K Smyth <smyth at wehi.edu.au> wrote:
> Dear Endre,
>
> I suspect the reason you didn't get a rsponse to your original posting is
> that your questions are not very specific.
>
> Assuming that you have three replicate arrays comparing a control to a
> treatment, your analysis looks fine.
>
> I can't give you any response to the problem reading ArrayVision format
> because you haven't shown us the error you received or the structure of
> your data files. Therefore we can't see if your files really are in
> ArrayVision format or diagnose what the read problem is.
>
> I can't tell you if the column names are correct, because ArrayVision
> columns are used-defined. Your interpretation appears reasonable.
>
> You ask if your design is correct, but you don't give any information
> about your experiment, eg the targets information. I have to assume that
> you have three replicate arrays.
>
> In my opinion, there is no good way to combine irregular numbers of
> within-array gene replicates, especially if the probes are not indentical.
>
> Hope this helps
> Gordon
>
> > Date: Fri, 28 Mar 2008 12:51:39 +0100
> > From: "Endre Sebestyen" <endre.sebestyen at gmail.com>
> > Subject: [BioC] basic limma questions
> > To: Bioconductor <bioconductor at stat.math.ethz.ch>
> >
> > Again :
> >
> > Hi!
> >
> > I'm a beginner in limma and bioconductor, and I'd like to ask a few
> > basic questions.
> >
> > I wrote the following script :
> >
> > library(limma)
> > targets <- readTargets("Targets1.txt")
> > RG <- read.maimages(targets$FileName, columns=list(R="CtrlVol",
> > G="DataVol", Rb="CtrlBg", Gb="DataBg"),
> > annotation=c("ID","Name","Rep"))
> > RG$genes <- readGAL("maize.gal")
> > RG$printer <- getLayout(RG$genes)
> > spottypes <- readSpotTypes()
> > RG$genes$Status <- controlStatus(spottypes, RG)
> > bgCorr <- backgroundCorrect(RG, method="movingmin")
> > nWithin <-normalizeWithinArrays(bgCorr, method="loess")
> > nBetween <- normalizeBetweenArrays(nWithin, method="Aquantile")
> > design <- c(1,1,1)
> > isGene <- nBetween$genes$Status == "cDNA"
> > fit <- lmFit(nBetween[isGene, ], design)
> > fit <- eBayes(fit)
> > res <- topTable(fit, number=1000)
> > write.table(res, file="results24top1000.txt", sep="+++")
> >
> > First, limma didn't recognize the ArrayVision format, and I had to
> > parse the raw data and define the columns myself. Is it correct to
> > pass the CtrlVol to R, DataVol to G, etc? The other question is that
> > I'm not sure about the design. Cy3 was the treated, Cy5 the control,
> > but after I used the read.maimages function and defined the values
> > myself, this design should be OK. Am I right?
> >
> > Last question : how can I combine the replicates on a chip? I have
> > some genes with 2,3,etc replicates, but not all. This is the 46k maize
> > array from www.maizearray.org
> >
> > Thanks for any comment and help.
> >
> >
> > Endre Sebestyen
> >
> > --
> > Agricultural Research Institute of the Hungarian Academy of Sciences
> > Department of Applied Genomics
> > H-2462 Martonv?s?r, Brunszvik street 2.
>
--
Agricultural Research Institute of the Hungarian Academy of Sciences
Department of Applied Genomics
H-2462 Martonvásár, Brunszvik street 2.
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