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

[Gordon Robertson]

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<mailto: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<http://www.bcgsc.ca/>



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--

Renaud Gaujoux
Computational Biology - University of Cape Town
South Africa

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