[NMF-user] setting the fraction of genes randomly sampled in an iteration?

[Renaud Gaujoux]

Could you please post some reproducible example (commands, output of
errors, traceback and sessionInfo)?
This will simplify tracing the issue.
If confidentiality is an issue, email only to me.

e.g.:

# run NMF
res <- nmf(x, 2:6, .opt='v9')
traceback()
sessionInfo()

Thank you.
Renaud


2013/3/18 Gordon Robertson <grobertson at bcgsc.ca>

> Renaud,
>
> Thanks for clarifying this.
>
> I asked because I tried to run NMF on a miRNA-seq abundance matrix that
> had 66 samples (columns) and only a small set of miRs (rows), say 20 miRs.
> I've used NMF routinely for larger miRNA-seq data matrices for some time
> (using 200-300 miRs), including on a 300-miR matrix for the same samples,
> but this time the survey returned only errors. I was able to get results
> from Matt Wilkerson's Consensus Cluster Plus package. I'll look more
> carefully at what happens to the NMF runs as I progressively remove miRs.
>
> G
>
>
>
> On 2013-03-18, at 12:55 AM, Renaud Gaujoux wrote:
>
> Hi,
>
> no, all genes/features are included in each run. What changes is the seed,
> i.e. starting point, which is different and randomly generated at each run.
>
> Standard consensus clustering analysis would use a different set of
> _samples_ for each run. This is fine for evaluating the accuracy/stability
> of classification, but makes it difficult to link features to sample
> groups, since each run (vote) returns a somehow different set of
> component-specific feature: what set of features or basis components should
> be used? average? consensus?
> Would be nice to incorporate a function/option to  easily perform such
> analysis though.
>
> There is still some methodology to be developed around this point. A
> technical issue also arise in term of memory/speed, if one wants to compute
> complete feature consensus matrices.
> I am happy to hear/discuss on this.
> My time is currently very limited, although bringing the package back to
> CRAN is quite high on my todo list.
>
> Renaud
>
>
>
> 2013/3/14 Gordon Robertson <grobertson at bcgsc.ca>
>
>> From what I understand, in each iteration (of, say, 200) in a run, a
>> random subset of genes is used. Is it possible to set the fractional value
>> retained, e.g. 0.90, 0.95?
>> Thanks,
>> G
>>  --
>> Gordon Robertson
>> Michael Smith Genome Sciences Centre
>> BC Cancer Agency
>> Vancouver BC Canada
>> www.bcgsc.ca
>>
>>
>>
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>>
>
>
>
> --
>
> Renaud Gaujoux
> Computational Biology - University of Cape Town
> South Africa
>
>
>


-- 

Renaud Gaujoux
Computational Biology - University of Cape Town
South Africa
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