BSmooth(BSseq, ns = 70, h = 1000, maxGap = 10^8, parallelBy = c("sample", "chromosome"), mc.preschedule = FALSE, mc.cores = 1, keep.se = FALSE, verbose = TRUE)
BSseq
.mclapply
(should the tasks be prescheduled).mclapply
(the number of cores used).
Note that setting mc.cores
to a value greater than 1 is not
supported on MS Windows, see the help page for mclapply
.BSseq
, containing smoothed values and
optionally standard errors for these.
ns
and h
are passed to the locfit
function. The
bandwidth used is the maximum (in genomic distance) of the h
and a width big enough to contain ns
number of methylation
loci.The function uses the parallel package to do parallel computations. In order to use this, make sure your system have enough RAM, these are typically big objects. The computation can either be split by chromosome or by sample, which is better depends on the number of samples and how many concurrent smoothings may be done.
locfit
in the locfit package, as well as BSseq
.
## Not run:
# data(BS.chr22)
# BS.fit <- BSmooth(BS.chr22, verbose = TRUE)
# BS.fit
# ## End(Not run)
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