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LSNMF

Synopsis:

LSNMF is a modified version of NMF (non-negative matrix factorization), it focus on gene expression patterns analysis on microarray datasets. The major improvement of LSNMF algorithm over NMF is that it incorporate uncertainty estimates into the update rules, so it is much more stable over the possible noise in the datasets, and it also more sensitive to the real signals. LSNMF is implemented in LAM/MPI-based parallelized C++, it was designed for running on Beowulf clusters (the desktop version is also available). It is an open-source package, the source code is released under the GNU general public license (GPL).

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Documentation:

Related Software:

  • Bayesian Decomposition - A pattern recognition algorithm which uses Bayesian statistics and Markov chain Monte Carlo sampling to determine the physically significant basis vectors for a data set.
  • ClutrFree - A cluster viewer package available as a Java application, it provides essentially the ability to compare microarray clusters issued from different experiments. ClutrFree features a procedure to construct a tree from those clusters to infer which ones are more stable among different experiments. Also, ClutrFree displays genes and their memberships along with annotations and ontology.

Reference:

  • Guoli Wang, Andrew V. Kossenkov, Michael F. Ochs, LS-NMF: A modified non-negative matrix factorisation algorithm utilizing uncertainty estimates. BMC Bioinformatics 2006, 7:175.

Contact Information:

Guoli Wang
Biostatistics and Bioinformatics Facility
Fox Chase Cancer Center
Philadelphia, PA 19111