[BioC] processCGH in snapCGH package

[Sean Davis]

jhs1jjm at leeds.ac.uk wrote:
> R 2.5.0 on openSUSE 10.2 x86_64.
> Hi,
> 
> I'm using the snapCGH package to analyse 2* 244k agilent CGH arrays with the aim
> of identifying regions of gain/loss.
> So far i've done the following:
> 
>> targets <- readTargets ("targets.txt")
>> RG1 <-read.maimages (targets$File_names, source="agilent")
>> RG2 <- readPositionalInfo (RG1,source="agilent")
>> RG2$design <- c(-1-1)
>> RG3 <- backgroundCorrect (RG2,method="minimum")
>> MA1 <- normalizeWithinArrays (RG2,method="median")
> 
> then
>> MA2 <- processCGH(MA1,method.of.averaging=mean,ID="MA1$genes$ProbeName")
> Error in order(na.last, decreasing, ...) :
>         argument 2 is not a vector
> 
> I've looked at ?processCGH and am following the vignette for the snapCGH package
> fairly closely. Can anyone help with the error.

You can't quote variable names like above.  I'm not sure that is going
to fix the problem, but until the syntax is correct, it will be hard to
diagnose the issue.

> Also i'm unsure of what background correction to use and normalization function
> (I've been informed that non-linear methods are unsuitable). Also if anyone has
> any experience of Agilent CGH arrays could they also tell me whether the
> default estimates used for the foreground and background intensities in
> read.maimages are suitable. I'd like to determine the most suitable methods
> before as I think the segmentation may take some time on my machine. If its a
> case of trial and error then then thats fine. Thanks for any input.

I would use the LogRatio column of the Agilent file without any further
normalization.  The LogRatio is already background corrected.  The CGH
algorithms in snapCGH do not depend on the center of the data, so there
isn't really a need to do any further median centering, etc.  In fact,
there are probably better methods to center the data, but these use the
segmented data.

Hope that helps.

Sean