| Title: | Parallel implementation of the "segment" function of package "DNAcopy" |
|---|---|
| Description: | Parallelized version of the "segment" function from Bioconductor package "DNAcopy", utilizing multi-core computation on host CPU |
| Authors: | Alex Krasnitz, Guoli Sun |
| Maintainer: | Guoli Sun <[email protected]> |
| License: | GPL-2 |
| Version: | 2.0 |
| Built: | 2024-11-26 05:22:14 UTC |
| Source: | https://github.com/cran/ParDNAcopy |
segment function of DNAcopy
There are three key differences between this function and the original
segment function of package DNAcopy. First, the execution can be
parallelized, either by using multiple cores of the present host or by
invoking a grid engine to run on multiple hosts. Secondly, random number
generator may be re-initialized, with the same seed, for each sample. Finally,
there is a "skinny" option for the value, i.e., a DNAcopy object with no
data item.
parSegment(CNAobj, ranseed = NULL, distrib = c("vanilla", "Rparallel"), njobs = 1, out = c("full", "skinny"), ...)parSegment(CNAobj, ranseed = NULL, distrib = c("vanilla", "Rparallel"), njobs = 1, out = c("full", "skinny"), ...)
CNAobj |
An object of class |
ranseed |
A single integer to seed the random number generator. |
distrib |
One of "vanilla" (default) and "Rparallel" to choose a parallelization option: no parallelization ("vanilla"), parallelization on multiple cores of the local host ("Rparallel"). |
njobs |
An integer specifying the desired number of parallel jobs. |
out |
One of "full" (default) or "skinny" to specify the form of the value, an object
of class |
... |
Arguments other than |
An object of class DNAcopy. If out == "skinny" the data
item of the value will not be returned in order to reduce the memory use.
Alex Krasnitz
Package DNAcopy.
data(coriell) #prepare data for segmentation CNA.object <- CNA(genomdat=coriell[,c(4,5)],coriell$Chromosome,coriell$Position, data.type="logratio",sampleid=dimnames(coriell)[[2]][4:5]) #equivalent to "segment" of DNAcopy parseg<-parSegment(CNA.object,undo.splits="sdundo") #Random number generator to be re-seeded for each sample parsegrep<-parSegment(CNA.object,ranseed=123,undo.splits="sdundo") #multi-core execution but the result should not change parsegrep1<-parSegment(CNA.object,ranseed=123,distrib="Rparallel",njobs=2, undo.splits="sdundo")data(coriell) #prepare data for segmentation CNA.object <- CNA(genomdat=coriell[,c(4,5)],coriell$Chromosome,coriell$Position, data.type="logratio",sampleid=dimnames(coriell)[[2]][4:5]) #equivalent to "segment" of DNAcopy parseg<-parSegment(CNA.object,undo.splits="sdundo") #Random number generator to be re-seeded for each sample parsegrep<-parSegment(CNA.object,ranseed=123,undo.splits="sdundo") #multi-core execution but the result should not change parsegrep1<-parSegment(CNA.object,ranseed=123,distrib="Rparallel",njobs=2, undo.splits="sdundo")