Bumphunter and minfi
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@matthias-zilbauer-5782
Last seen 10.2 years ago
Dear all, I am using the minfi package to pre-process my K450 methylation data as well as to test for differentially methylated probes/positions (dmps). However, I would also like to identify differentially methylated regions (dmrs) and have tried the MethyAnalysis package for this. Does anyone know how to use bumphunter for minfi data or alternatively how to coerce an RGset object into a GenoSet object? Any suggestions and help would be much appreciated. Many thanks in advance Matt ==================================== Matthias Zilbauer MD PhD MRCPCH Clinical lecturer in Paediatric Gastroenterology Department of Paediatric Gastroenterology Box 267, Addenbrooke's Hospital Hills Road, Cambridge, CB2 0QQ Lab: Adult and Paediatric Gastroenterology Research Unit Level 7, Addenbrooke's Hospital Hills Road, Cambridge, CB2 0QQ [[alternative HTML version deleted]]
genoset minfi bumphunter genoset minfi bumphunter • 1.9k views
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@matthias-zilbauer-5782
Last seen 10.2 years ago
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the obvious thing to do would be to use minfi's mapToGenome function: require(minfi) require(minfiData) dat <- preprocessIllumina(RGsetEx, bg.correct=T, normalize="controls") mapped <- mapToGenome(dat) and then coerce the resulting SummarizedExperiment to a genoset: mgset <- as(mapped, 'MethyGenoSet') ## Error in as(mapped, "MethyGenoSet") : ## no method or default for coercing "GenomicMethylSet" to "MethyGenoSet" That's a shame, because I added coercions in methylumi-dev that go from MethyLumiSet/MethyLumiM objects to SummarizedExperiments (GenomicMethylSet is just a subclass of SummarizedExperiment), and it would make sense to have a coercion to/from genoset-derived objects and SummarizedExperiment objects. All of these things serve a common purpose: to map loci to the genome. The only thing that's different is the precise mechanism, and I don't think that's really a showstopper. All of the packages that deal with DNA methylation (methylumi, methyAnalysis, minfi, bsseq, QuasR) eventually return an object that reflects how much evidence there is for methylation at a given genomic position (or, in some cases, a range of positions -- a similar basic problem). I'll look into how annoying (or not) it would be to write this plumbing, mostly since I use all of the above on a regular basis, and have a small stack of partially-responded-to emails from this list that could be addressed thusly. Best, --t On Thu, Feb 28, 2013 at 3:32 AM, Zilbauer Matthias <mz304@medschl.cam.ac.uk>wrote: > Dear all, > I am using the minfi package to pre-process my K450 methylation data as > well as to > test for differentially methylated probes/positions (dmps). However, I > would also like to identify > differentially methylated regions (dmrs) and have tried the MethyAnalysis > package for this. > > Does anyone know how to use bumphunter for minfi data or alternatively how > to > coerce an RGset object into a GenoSet object? > > Any suggestions and help would be much appreciated. > Many thanks in advance > > Matt > > > > > > ==================================== > Matthias Zilbauer MD PhD MRCPCH > Clinical lecturer in Paediatric Gastroenterology > Department of Paediatric Gastroenterology > Box 267, Addenbrooke's Hospital > Hills Road, Cambridge, CB2 0QQ > > Lab: > Adult and Paediatric Gastroenterology Research Unit > Level 7, Addenbrooke's Hospital > Hills Road, Cambridge, CB2 0QQ > > > > > > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor@r-project.org > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > -- *A model is a lie that helps you see the truth.* * * Howard Skipper<http: cancerres.aacrjournals.org="" content="" 31="" 9="" 1173.full.pdf=""> [[alternative HTML version deleted]]
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