[BioC] rma for tiling arrays (oligo package)
James W. MacDonald
jmacdon at med.umich.edu
Mon Jul 21 17:15:24 CEST 2008
Thanks Ben, I forgot that you moved everything into preprocessCore.
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.
> 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.
>> 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.
>>> Code and session info is here:
>>>  3092374 12
>>>  3092338 12
>>>  3092374
>>>  2921991
>>>  2921991 12
>>> 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
>>> R version 2.6.0 (2007-10-03)
>>> attached base packages:
>>>  splines tools stats graphics grDevices utils datasets
>>>  methods base
>>> other attached packages:
>>>  pd.at35b.mr.v04.2.tigrv5_1.2.0 oligo_1.2.2
>>>  oligoClasses_1.0.3 affxparser_1.10.2
>>>  AnnotationDbi_1.0.6 preprocessCore_1.0.0
>>>  RSQLite_0.6-9 DBI_0.2-4
>>>  Biobase_1.16.3
>>> loaded via a namespace (and not attached):
>>>  rcompgen_0.1-17
>>> Bioconductor mailing list
>>> Bioconductor at stat.math.ethz.ch
>>> Search the archives:
>> James W. MacDonald, M.S.
>> Hildebrandt Lab
>> 8220D MSRB III
>> 1150 W. Medical Center Drive
>> Ann Arbor MI 48109-0646
>> Bioconductor mailing list
>> Bioconductor at stat.math.ethz.ch
>> Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor
James W. MacDonald, M.S.
8220D MSRB III
1150 W. Medical Center Drive
Ann Arbor MI 48109-0646
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