[BioC] Yeast 2.0 Arrays

[Mike Walter]

Hi there,

I have a question on Affymetrix Yeast 2.0 arrays. These arrays contain about 5000 probesets for budding and fission yeast, respectively. We hybridized budding yeast sample and now I'd like to get rid of all the fission yeast probes before normalization. There is a mask file outlining which probesets belong to which organism. However, when I use ReadAffy(..., rm.mask=T) the number of probes does not change (s. below). Is there a way to specify a mask file during the affybatch import?

Any hints are welcome.

Mike

> d1 <- ReadAffy(celfile.path=celfile, filenames=filenames, rm.mask=F)
> d2 <- ReadAffy(celfile.path=celfile, filenames=filenames, rm.mask=T)
> dim(pm(d1))
[1] 120855      5
> dim(pm(d2))
[1] 120855      5
> sessionInfo()
R version 2.10.1 (2009-12-14) 
i386-pc-mingw32 

locale:
[1] LC_COLLATE=German_Germany.1252  LC_CTYPE=German_Germany.1252   
[3] LC_MONETARY=German_Germany.1252 LC_NUMERIC=C                   
[5] LC_TIME=German_Germany.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] yeast2cdf_2.5.0      affyQCReport_1.24.0  lattice_0.18-3      
 [4] RColorBrewer_1.0-2   affyPLM_1.22.0       preprocessCore_1.8.0
 [7] xtable_1.5-6         simpleaffy_2.22.0    gcrma_2.18.1        
[10] genefilter_1.28.2    affy_1.24.2          Biobase_2.6.1       

loaded via a namespace (and not attached):
 [1] affyio_1.14.0       annotate_1.24.1     AnnotationDbi_1.8.2
 [4] Biostrings_2.14.12  DBI_0.2-5           grid_2.10.1        
 [7] IRanges_1.4.16      RSQLite_0.9-1       splines_2.10.1     
[10] survival_2.35-8     tools_2.10.1       
> 

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-----Ursprüngliche Nachricht-----
Von: Robert Castelo <robert.castelo at upf.edu>
Gesendet: 08.07.2010 13:16:16
An: "Hernando Martínez" <hernybiotec at gmail.com>
Betreff: Re: [BioC] removal of genes with low expression values

>Hernando,
>
>if by removing genes with low expression values you mean removing genes
>that are not expressed or have an undetectable level of expression with
>the microarray instrument employed, the issue is not as easy as it may
>look like if you need to do it very accurately because different genes
>may behave differently due to complicated probe-specific effects.
>
>i would encourage you to take a look at this publication:
>
>Zilliox MJ, Irizarry RA
>A gene expression bar code for microarray data.
>Nat Methods. 2007 Nov;4(11):911-3.
>http://www.ncbi.nlm.nih.gov/pubmed/17906632
>http://rafalab.jhsph.edu/barcode
>
>
>i'm not the authority about this, and the authors of the work could give
>you a more specific advice, but i'd say that the take-home message is
>that if you have a sufficiently large panel of biological replicates for
>a variety of cellular states, try to use them to find a gene-dependent
>threshold of expression under the assumption that only a small fraction
>of genes is expressed under a specific cellular state.
>
>cheers,
>robert.
>
>
>
>On Wed, 2010-07-07 at 11:28 +0100, Hernando Martínez wrote:
>> Hi, I need to remove genes with low expression values from a expression
>> matrix. I would like to remove those with an average of expression values
>> less than a certain cut-off. I was thinking in computing the average for
>> each row, create a list with the gene names for which their average is less
>> than the cut-off, and remove those genes from the initial matrix. However, I
>> have a couple of doubts that maybe you can help me with. Is there any
>> package or function that makes this easier? And, does anyone know which
>> cut-off to use for data normalized with RMA and for data normalized with
>> MAS5? Thanks,
>> 
>> 
>> _______________________________________________
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>
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