Re: gcRMA: problem compute.affinities.local on gngnf1musa

Hi Julien,

Julien Roux wrote:
> Hello list,
> 
> In *Schuster et al. 2007 (http://genomebiology.com/2007/8/6/R125) a 
> method is presented allowing to correct *MAS5 present/absent calls based 
> on gcRMA transformed PM threshold values.
> The R script is available in sup data at 
> http://genomebiology.com/content/supplementary/gb-2007-8-6-r125-s1.txt
> 
> When trying to run it on my data I am faced to an error:
>  > data
> AffyBatch object
> size of arrays=854x854 features (11 kb)
> cdf=gnGNF1Musa (36182 affyids)
> number of samples=16
> number of genes=36182
> annotation=gngnf1musa
> notes= >  ai <- compute.affinities.local(data, Array=NULL)
> Adjusting for optical effect................Done.
> Computing base-position profiles for probe affinitiesErreur dans 
> complementSeq(seqs, start = 13, stop = 13) :
> Character N does not code for a nucleic acid.
> 
> I tried with other platforms (e.g. mgu74av2) and this works.
> So I guess this is due to an error in the annotation package gngnf1musa.
> I installed this package (custom array affymetrix) made available by Cei 
> Abreu-Goodger 
> (http://article.gmane.org/gmane.science.biology.informatics.conductor/13659) 
> at ftp://ftp.sanger.ac.uk/pub/cei/gngnf1_R_packages.tar.gz
> What can be wrong?
> 
> Then I tried:
>  > ai <- compute.affinities(cdfName(data))
> Computing affinities.Done.
> 
> This worked. However I am not sure it is doing the same thing (Adjusting 
> for optical effect? Computing base-position profiles for probe affinities?)
> What is the difference between compute.affinities and 
> compute.affinities.local?

 From the source for these functions:

##this is almost the same as compute.affinities
##except that affinity.spline.coefs is not loaded with data()
##but computed using the data provided by the user

So I have to assume that the probe package for your chip has some probes 
in which Affy used the 'N' IUPAC symbol. Since gcrma doesn't understand 
anything but ACTG, this causes the error.

So when you use compute.affinities(), you load the pre-calculated 
affinity data rather than using the sequences from your chip. Hence no 
error.

Best,

Jim

> 
> Thanks for your help to clarify this.
> Julien
> 
>  > sessionInfo()
> R version 2.7.0 (2008-04-22)
> i386-apple-darwin8.10.1
> 
> locale:
> C
> 
> attached base packages:
> [1] splines   tools     stats     graphics  grDevices utils     datasets
> [8] methods   base   
> other attached packages:
> [1] gngnf1musaprobe_1.8.1 gngnf1musacdf_1.14.0  gcrma_2.12.0        [4] 
> matchprobes_1.12.0    affy_1.18.0           preprocessCore_1.2.0
> [7] affyio_1.8.0          Biobase_2.0.1      

--

-- 
James W. MacDonald, M.S.
Biostatistician
Affymetrix and cDNA Microarray Core
University of Michigan Cancer Center
1500 E. Medical Center Drive
7410 CCGC
Ann Arbor MI 48109
734-647-5623

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