Just to set the record straight, WGCNA is a CRAN package.
As to Ankush's question - the current WGCNA version does not support
analysis of more than about 46300 nodes (probes) in one block. You
have two options: 1. filter out some of the least-informative probes
(e.g., probes with lowest mean expression or lowest variance); 2. use
the "blockwise" approach as implemented in blockwiseModules. Set the
maxBlockSize argument to say 40000, and the function will
automatically split your data into 2 blocks and run the analysis in
each block separately.
The third option is to wait a few weeks (possibly months), I do have a
WGCNA update in the works that __should__ work on blocks larger than
46300.
Best,
Peter
On Fri, Feb 3, 2017 at 7:31 AM, Bert Gunter <bgunter.4567 at gmail.com>
wrote:
Probably wrong list. Try the Bioconductor list instead.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Fri, Feb 3, 2017 at 3:19 AM, Ankush Sharma <ankush.sak at gmail.com>
Hi all ,
I'm working on WGCNA on R-3.3.1 version to reconstruct gene -gene
coexpression networks of 54000 probes in 230 samples on Load Sharing
facility (Remote computing cluster). Despite memory at dispose, I'm
encountering a error of allocation of memory at soft thresholding step
at TOM Similarity step. The problem of memory allocation at soft
thresholding step was corrected by allocating the required memory
-R "rusage[mem=40000]".
Error Message
> # Turn adjacency into topological overlap
TOM = TOMsimilarity(adjacency);
Error in TOMsimilarity(adjacency) :
long vectors (argument 1) are not supported in .Fortran
Calls: TOMsimilarity -> .C
Execution halted
Warning message:
system call failed: Cannot allocate memory
Is there a way to run build this TOMsimilarity matrix.
Thanks
Best Regards,
Ankush Sharma,PhD
Visiting CASyM Postdoctoral Research fellow (CASyM Consortium, EU-FP7)
LISM, Institute of Clinical Physiology, Siena (Italy)
Experimental Oncology Unit (UOS),
I
nstitute of Clinical Physiology
- National Research Council,
Siena (IT)
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