Hi Paolo,

too bad, you were almost there! When MEDIPS stopped processing due to
memory limitations, differential coverage was already calculated.
Unfortunately, the last step, i.e. creating the output result table, was
too memory intensive for your set up. May I ask how many samples of which
species do you process and what is the chosen window size? These are the
parameters that influence memory requirements for the differential coverage
analysis.

While I will investigate, how to further reduce memory requirements in
future versions, I see two immediate possible solutions without reducing
window and sample sizes: i) migrate your analysis to a cluster with more
memory, ii) analyze your data in chunks. While I understand that i) is not
always available, this is what you can try for solution ii):

Update to MEDIPS version >= 1.11.16. This is currently available at
http://www.bioconductor.org/packages/2.13/bioc/html/MEDIPS.html and will be
available as version 1.12.0 with the release of Bioconductor 2.13 on
October 15th 2013. In MEDIPS version >= 1.11.16, the function MEDIPS.meth()
has the parameter "chr" which allows to process only a set of selected
chromosomes. In your case, I expect that it will be sufficient to divide
the genome into two groups of chromosomes. Therefore, you can try running
the MEDIPS.meth() function twice like:

res = MEDIPS.meth(MSet1 = MSets_groupA, MSet2 = MSets_groupB, chr =
chr_names(MSets_groupA[[1]])[1:x], ...)
resB = MEDIPS.meth(MSet1 = MSets_groupA, MSet2 = MSets_groupB, chr =
chr_names(MSets_groupA[[1]])[x+1:n], ...)

where n is the number of chromosomes included in your MEDIPS Sets and x is
an arbitrary number that divides your chromosomes into two groups (e.g.
round(n/2)). Please note that some modeled parameters (e.g. for library
size normalization) will be slightly different for two subsets of the data
compared to processing a genome wide table at once.

Finally, you can combine the result tables by

res = rbind(res, res_B)
rm(res_B)

and continue with a normal workflow.

All the best,
Lukas






On Wed, Oct 9, 2013 at 3:33 AM, Paolo Kunderfranco <
paolo.kunderfranco@gmail.com> wrote:

> Dear All,
> I am facing some problems with MEDIPS package,
> I Think I'am running out of memory once I run the command MEDIPS.meth
> ................
> Adjusting p.values for multiple testing...
> Creating results table...
> Adding differential coverage results...
> Error: cannot allocate vector of size 207.9 Mb
> Inoltre: Warning messages:
> 1: In unlist(vlist, recursive = FALSE, use.names = FALSE) :
>   Reached total allocation of 24501Mb: see help(memory.size)
> 2: In unlist(vlist, recursive = FALSE, use.names = FALSE) :
>   Reached total allocation of 24501Mb: see help(memory.size)
> 3: In unlist(vlist, recursive = FALSE, use.names = FALSE) :
>   Reached total allocation of 24501Mb: see help(memory.size)
> 4: In unlist(vlist, recursive = FALSE, use.names = FALSE) :
>   Reached total allocation of 24501Mb: see help(memory.size)
>
> Is there a way to avoid this problem?
>
> I have a 24 Gb RAM workstation I don't see why it fails...
>
> Thanks,
> Paolo
>
>
> > sessionInfo()
> R version 3.0.0 (2013-04-03)
> Platform: x86_64-w64-mingw32/x64 (64-bit)
>
> locale:
> [1] LC_COLLATE=Italian_Italy.1252  LC_CTYPE=Italian_Italy.1252
> LC_MONETARY=Italian_Italy.1252 LC_NUMERIC=C
> LC_TIME=Italian_Italy.1252
>
> attached base packages:
> [1] parallel  stats     graphics  grDevices utils     datasets
> methods   base
>
> other attached packages:
> [1] MEDIPS_1.10.0        BiocInstaller_1.10.3 gtools_3.1.0
> DNAcopy_1.34.0       BSgenome_1.28.0      Biostrings_2.28.0
> GenomicRanges_1.12.4 IRanges_1.18.1       BiocGenerics_0.6.0
>
> loaded via a namespace (and not attached):
>  [1] biomaRt_2.16.0   bitops_1.0-6     edgeR_3.2.4      limma_3.16.8
>   RCurl_1.95-4.1   Rsamtools_1.12.4 stats4_3.0.0     tools_3.0.0
> XML_3.98-1.1     zlibbioc_1.6.0
>

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