[BioC] rma for tiling arrays (oligo package)

[James W. MacDonald]

Thanks Ben, I forgot that you moved everything into preprocessCore.

Best,

Jim



Ben Bolstad wrote:
> Actually, you can avoid "copying from affy" altogether by using
> preprocessCore directly where both normalize.quantiles() and 
> rma.background.correct() are actually defined. 
> 
> I think oligo also loads preprocessCore, so those functions should
> already be exposed.
> 
> Ben
> 
> 
> 
> 
> 
> On Mon, 2008-07-21 at 10:48 -0400, James W. MacDonald wrote:
>> Hi Ann,
>>
>> I don't think you want to use rma() directly, as it is going to try to 
>> do a medianpolish on probesets but such a thing doesn't exist for the 
>> tiling arrays.
>>
>> If you want to use the background correction and normalization that are 
>> used by rma() then I think it will take some work on your part. The 
>> functions you will want to use are part of the affy package, but you 
>> don't really want to load affy and oligo at the same time because there 
>> are so many identically named functions (they both have namespaces, so 
>> this isn't the end of the world, but it is easier if you don't have to 
>> deal with name collisions).
>>
>> I would personally just copy the functions normalize.quantiles() and 
>> rma.background.correct() from affy into a file (say, affysources.R) and 
>> then source that into R. Both of these functions want you to pass a 
>> matrix, so you would want to extract the pm data from your AllArrays 
>> object, run rma.background.correct() and then normalize.quantiles() on 
>> the matrix, and then put that back into AllArrays.
>>
>> Best,
>>
>> Jim
>>
>>
>>
>> Ann Hess wrote:
>>> After creating an appropriate library using the makePDpackage, I am 
>>> using the oligo package to open and work with Affymetrix Arabidopsis 
>>> Tiling 1.0R Arrays.  I am interested in using the rma function to 
>>> background correct and normalize the data, but I am not sure how to map 
>>> the processed data back to probes or directly to chromosome and position.
>>>
>>> What do the rownames of the expression matrix created by rma correspond 
>>> to?  My best guess is that they correspond to chromosome position (which 
>>> can be found using pmChr, but not for an ExpressionSet object).  
>>> However, these positions are relative to a particular chromosome and 
>>> therefore not unique.  For example, there are probes corresponding to 
>>> position 417 on both Chromosome 3 and Chromosome 5, but only a single 
>>> row in the ExpressionSet object corresponding to 417.
>>>
>>> Is there a way to background correct and normalize the data without the 
>>> rma function?  Perhaps this would allow for easier mapping to probes.
>>>
>>> Any suggestions would be appreciated.
>>>
>>> Ann
>>>
>>> Code and session info is here:
>>>
>>>> library(oligo)
>>>> library(pd.at35b.mr.v04.2.tigrv5)
>>>> AllArrays<-read.celfiles(list.celfiles(),pk="pd.at35b.mr.v04.2.tigrv5")
>>>> dim(pm(AllArrays))
>>> [1] 3092374      12
>>>> dim(mm(AllArrays))
>>> [1] 3092338      12
>>>
>>>> Pos<-pmPosition(AllArrays)
>>>> length(Pos)
>>> [1] 3092374
>>>> length(unique(Pos))
>>> [1] 2921991
>>>
>>>> RMAout<-rma(AllArrays)
>>>> dim(exprs(RMAout))
>>> [1] 2921991      12
>>>
>>>> exprs(RMAout)[1:10,1:2]
>>>          Comp5-1_1006.CEL Comp5-2_1006.CEL
>>> 0                3.344400         3.295634
>>> 1                1.988137         1.708682
>>> 1000             6.315857         7.297425
>>> 10000009         9.053133         8.754469
>>> 10000014         2.106050         2.137780
>>> 10000024        10.392988         9.385502
>>> 10000026         2.242264         5.487639
>>> 10000034         1.830658         5.239400
>>> 1000004          3.097441         5.825040
>>> 10000046         6.839724         7.221181
>>>
>>>> sessionInfo()
>>> R version 2.6.0 (2007-10-03)
>>> x86_64-redhat-linux-gnu
>>>
>>> attached base packages:
>>> [1] splines   tools     stats     graphics  grDevices utils     datasets
>>> [8] methods   base
>>>
>>> other attached packages:
>>> [1] pd.at35b.mr.v04.2.tigrv5_1.2.0 oligo_1.2.2
>>> [3] oligoClasses_1.0.3             affxparser_1.10.2
>>> [5] AnnotationDbi_1.0.6            preprocessCore_1.0.0
>>> [7] RSQLite_0.6-9                  DBI_0.2-4
>>> [9] Biobase_1.16.3
>>>
>>> loaded via a namespace (and not attached):
>>> [1] rcompgen_0.1-17
>>>
>>> _______________________________________________
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>> -- 
>> James W. MacDonald, M.S.
>> Biostatistician
>> Hildebrandt Lab
>> 8220D MSRB III
>> 1150 W. Medical Center Drive
>> Ann Arbor MI 48109-0646
>> 734-936-8662
>>
>> _______________________________________________
>> Bioconductor mailing list
>> Bioconductor at stat.math.ethz.ch
>> https://stat.ethz.ch/mailman/listinfo/bioconductor
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> 

-- 
James W. MacDonald, M.S.
Biostatistician
Hildebrandt Lab
8220D MSRB III
1150 W. Medical Center Drive
Ann Arbor MI 48109-0646
734-936-8662