I would also like to run segmentation in parallel, but how do you do this if you are using a separate reference set.
This is what I am running in a single process (that I would like to parallelize): cbs <- CbsModel(cesN, reference) ce <- ChromosomeExplorer(cbs) process(ce, chromosomes = 1:23, zooms = c(1, 16)) Could I do the same as your previous response, i.e. have each processor extract out a subset of the arrays and process them with the above, then run the above on a single CPU over all arrays to get the final results (which should run fast since all the computationally intensive intermediate results will have been memoized on disk)? Overall, I am running the first 4 steps of the CRMAv2 vignette (http://www.aroma-project.org/vignettes/CRMAv2) and then the above for segmentation. I want to parallelize this, and my strategy is to have each processor extract a subset of the arrays and run this on the subset, then run it again on a single CPU for all the arrays. And I'm doing the parallelization using the multicore package's mclapply. Does this seem okay or would you recommend any changes? thanks, Andrew Smith On Friday, December 3, 2010 1:18:23 AM UTC-5, Henrik Bengtsson wrote: > > Hi. > > On Thu, Dec 2, 2010 at 10:24 AM, Kai <wang...@gmail.com <javascript:>> > wrote: > > Hi Henrik, > > > > I was trying to run segmentation on a large set of ~300 SNP genotyping > > array profiles. Currently I am loading all the profiles into aroma and > > run the segmenter on them one by one, which takes a really long time. > > I was wondering whether there is a way to break the computation into > > parts and run all the parts simultaneously. Specifically: > > > > 1) Is there a way to load only a subset of profiles in a project into > > a "AromaUnitTotalCnBinarySet"? > > It is true that ds <- AromaUnitTotalCnBinarySet$byName(...) will setup > a set containing all data files. However, after that you can always > subset using extract(), e.g. ds <- extract(ds, 1:5); > > > 2) Is there a way to run segmentation on single, or a subset of > > profiles in a "AromaUnitTotalCnBinarySet"? > > Yes, either by subsetting as above already from start or simply by > specifying the 'arrays' argument to fit()/process() [below]. Note > that the latter is a more convenient approach for various reasons. > First, if the reference used to calculate CN ratios is the robust > average across all samples, then you do not have to worry about > getting it correct. (This is not a problem in your particular case > because you use that cbs$.calculateRatios <- FALSE feature). Second, > the final ChromosomeExplorer HTML page correctly list all samples. If > you subset immediately after setting up the data set (as above), then > you basically have to make sure to process() one ChromosomeExplorer on > all arrays. > > > 3) Assuming that one can generate the CBS segmentation model on single > > profiles, is there a way to load them together back in to aroma and > > pass to the "ChromosomeExplorer"? > > Yes. The simplest way is to simply run what you are doing below ones > at the very end. Already segmented and process samples will be > skipped, also already generated image files etc. > > > > > The current process I have (which performs segmentation one sample at > > a time) is implemented as follows: > > > > # segment by CBS model > > ds = AromaUnitTotalCnBinarySet > > $byName("dataset,paired",chipType="HumanOmni1-Quad"); > > > > cbs = CbsModel(ds); > > cbs$.calculateRatios = FALSE; > > > > fit(cbs, chromosomes=c(1:23), min.width=5, undo.splits="sdundo", > > undo.SD=1, verbose=2); > > > > # display data and segmentation in ChromosomeExplorer > > ce = ChromosomeExplorer(cbs); > > process(ce,chromosomes=c(1:23)); > > > > Any other suggestion you may provide is also highly appreciated. Thank > > you very much. > > library("aroma.core"); > verbose <- Arguments$getVerbose(-4, timestamp=TRUE); > > # Arrays that your host should process > arrays <- 5:8; # Change for different hosts > > # Setup the complete data set > ds <- > AromaUnitTotalCnBinarySet$byName("dataset,paired",chipType="HumanOmni1-Quad"); > > # Setup the "complete" segmentation model > cbs <- CbsModel(ds, min.width=5, undo.splits="sdundo", undo.SD=1); > cbs$.calculateRatios <- FALSE; > > # Fit a subset of the arrays > fit(cbs, arrays=arrays, chromosomes=c(1:23), verbose=verbose); > > # Setup the "complete" ChromosomeExplorer, ... > ce <- ChromosomeExplorer(cbs); > > # ...but generate PNG image files only for a subset > process(ce, arrays=arrays, chromosomes=c(1:23), verbose=verbose); > > Note that you actually do not have to call fit() explicitly, because > process() will do it implicitly (with the same arguments). > > If you want to call the above script from the command line, then > replace the arrays <- ... line with > > arrays <- commandArgs(asValue=TRUE)$arrays; > arrays <- eval(parse(text=arrays)); > arrays <- Arguments$getIndices(arrays); > > and then you can run the above by: > > R --args --arrays=1:5 < script.R > > Hope this helps > > Henrik > > > > > Best, > > Kai > > > > -- > > When reporting problems on aroma.affymetrix, make sure 1) to run the > latest version of the package, 2) to report the output of sessionInfo() and > traceback(), and 3) to post a complete code example. > > > > > > You received this message because you are subscribed to the Google > Groups "aroma.affymetrix" group with website http://www.aroma-project.org/ > . > > To post to this group, send email to > > aroma-af...@googlegroups.com<javascript:> > > To unsubscribe and other options, go to > http://www.aroma-project.org/forum/ > > > > -- -- When reporting problems on aroma.affymetrix, make sure 1) to run the latest version of the package, 2) to report the output of sessionInfo() and traceback(), and 3) to post a complete code example. 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