[BioC] affyPara: background correction & normalization only?
schmidb at ibe.med.uni-muenchen.de
Fri Mar 5 13:02:46 CET 2010
I did some changes to preproPara(). No there is a summarization method
'none' (summary.method='none') available. There will be no summarization
step and the results object eset is NULL.
I submitted these changes and documentation to the svn. Version 1.7.1.
should be available ad midnight:
Now at all nodes the bgc and normalized affyBatches are available in the
GlobalEnvironment. It is very simple to run some code on that.
res <- clusterCall(cluster, FUN)
if (exists("AffyBatch", envir = .GlobalEnv))
AffyBatch <- get("AffyBatch", envir = .GlobalEnv)
# do anything you want on the AffyBatch.
res will be a list of results from all nodes. You have to find a way to
combine these results.
Leo Lahti wrote:
> Dear affyPara package maintainers and BioC developer community,
> The parallelizations of Affy preprocessing in the affyPara package
> provide essential tools to handle large array collections.
> Before starting to hack on this myself, I would like to ask if there
> are workarounds in affyPara to obtain a preprocessed & normalized (but
> not summarized) PM intensity matrix from CEL files? Alternatively,
> having an access to virtual affybatch (i.e. keeping it in the nodes
> without 'rebuild') would solve the problem. Is such functionality
> I would need the probe-level values (for PM probes) after
> preprocessing and normalization (but without probeset summarization
> step) - in an ideal case a probes x arrays matrix, and not
> necessarily other information from the affybatch object. It seems that
> both background correction and normalization can be done in affyPara
> by reading in the CEL files directly. However, the output of these
> methods in itself an affybatch which will cause the memory problems
> the package is trying to solve.
> Thanks once more for relevant work.
> with kind regards
> Leo Lahti
> Department of Information and Computer Science
> Aalto University School of Science and Technology
Dr. rer. nat. Markus Schmidberger
IBE - Institut für medizinische Informationsverarbeitung,
Biometrie und Epidemiologie
Lehrstuhl für Biometrie und Bioinformatik
Marchioninistr. 15, D-81377 Muenchen
Mail: Markus.Schmidberger [at] ibe.med.uni-muenchen.de
More information about the Bioconductor