[BioC] limma Within Array Normalisation By Controls

Gordon K Smyth smyth at wehi.EDU.AU
Wed Jan 26 00:11:24 CET 2011


Dear Dario,

In truth, limma shouldn't need to know the layout for "control" 
normalization.  I'll change the code to remove the check in the future.

In the meantime, you can set

   RG$printer <- list(ngrid.r=1, ngrid.c=1,
     nspot.r=nrow(RG), nspot.c=ncol(RG))

then the code will work fine.

However, I suspect that the Nimblegen probes marked "random" may actually 
be negative control probes, whereas control normalization requires 
positive control probes covering a wide range of intensities.  Nimblegen 
arrays usually have an annotation column called ControlType, which is 
equal to 0 for negative controls.  You can also view where the "random" 
probes fall using plotMA().  If the control probes are all at the lowest 
intensities, then they are not suitable for use with control 
normalization.  On the other hand, you could still make use of the fact 
that these probes shouldn't change between samples, by using "loess" 
normalization and upweighting these probes.

BTW, the reason why the layout isn't set automatically is that limma 
doesn't have a read method for Nimblegen arrays, so you probably read the 
data using source="generic", so limma doesn't know whether it's a new 
commercial array or an old spotted array.

Best wishes
Gordon

> Date: Tue, 25 Jan 2011 13:00:29 +1100 (EST)
> From: Dario Strbenac <D.Strbenac at garvan.org.au>
> To: bioconductor at r-project.org
> Subject: [BioC] limma Within Array Normalisation By Controls
> Message-ID: <20110125130029.BKP14739 at gimr.garvan.unsw.edu.au>
> Content-Type: text/plain; charset=us-ascii
>
> Hello,
>
> I have an experiment where there are some Nimblegen 2.1 million probe 
> Mouse promoter arrays with IPs always in the red channel and input DNA 
> always in the green channel. I notice that the arrays have some probes 
> of type Random, which I assume should not be changing between channels. 
> So, I'd like to use normalizeWithinArrays with method = "control". I 
> call the method as :
>
> normalizeWithinArrays(RG, method = "control", controlspots = RG$genes$Status == "Random")
>
> and get the error :
>
> Error in normalizeWithinArrays(RG, method = "control", controlspots = RG$genes$Status ==  :
>  Layout argument not specified
>
> I'm confused as to why it requires the layout ? I didn't think newer array designs had print tip groups or replicate spots ?
>
> --------------------------------------
> Dario Strbenac
> Research Assistant
> Cancer Epigenetics
> Garvan Institute of Medical Research
> Darlinghurst NSW 2010
> Australia

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