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Fizzy: feature subset selection for metagenomics

BACKGROUND: Some of the current software tools for comparative metagenomics provide ecologists with the ability to investigate and explore bacterial communities using α- & β-diversity. Feature subset selection - a sub-field of machine learning - can also provide a unique insight into the differences between metagenomic or 16S phenotypes. In particular, feature subset selection methods can obtain the operational taxonomic units (OTUs), or functional features, that have a high-level of influence on the condition being studied. For example, in a previous study we have used information-theoretic feature selection to understand the differences between protein family abundances that best discriminate between age groups in the human gut microbiome. RESULTS: We have developed a new Python command line tool, which is compatible with the widely adopted BIOM format, for microbial ecologists that implements information-theoretic subset selection methods for biological data formats. We demonstrate the software tools capabilities on publicly available datasets. CONCLUSIONS: We have made the software implementation of Fizzy available to the public under the GNU GPL license. The standalone implementation can be found at http://github.com/EESI/Fizzy.

Identiferoai:union.ndltd.org:arizona.edu/oai:arizona.openrepository.com:10150/610268
Date January 2015
CreatorsDitzler, Gregory, Morrison, J. Calvin, Lan, Yemin, Rosen, Gail L.
ContributorsDepartment of Electrical & Computer Engineering, The University of Arizona, Department of Electrical & Computer Engineering, Drexel University, School of Biomedical Engineering, Science and Health, Drexel University
PublisherBioMed Central
Source SetsUniversity of Arizona
LanguageEnglish
Detected LanguageEnglish
TypeArticle
Rights© 2015 Ditzler et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/)
Relationhttp://www.biomedcentral.com/1471-2105/16/358

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