Omics Metadata Management Software (OMMS).

Autor:	Perez-Arriaga MO; Department of Computer Science, Mail stop: MSC01 1130, 1 University of New Mexico, Albuquerque, NM 87131-0001., Wilson S; Center for Advanced Research Computing, University of New Mexico, Albuquerque, NM 87131., Williams KP; Systems Biology, Sandia National Laboratories, Mail Stop 9291, Livermore, CA 94550., Schoeniger J; Systems Biology, Sandia National Laboratories, Mail Stop 9291, Livermore, CA 94550., Waymire RL; Security Systems Analysis, Sandia National Laboratories, Mail Stop 0757, Albuquerque, NM 87123., Powell AJ; Center for Advanced Research Computing, University of New Mexico, Albuquerque, NM 87131 ; Department of Biology, Mail stop: MSC03 2020, 1 University of New Mexico, Albuquerque, NM 87131-0001 ; Computational Simulation Infrastructure, Sandia National Laboratories, Mail Stop 0845, Albuquerque, NM 87123.
Jazyk:	angličtina
Zdroj:	Bioinformation [Bioinformation] 2015 Apr 30; Vol. 11 (4), pp. 165-72. Date of Electronic Publication: 2015 Apr 30 (Print Publication: 2015).
DOI:	10.6026/97320630011165
Abstrakt:	Unlabelled: Next-generation sequencing projects have underappreciated information management tasks requiring detailed attention to specimen curation, nucleic acid sample preparation and sequence production methods required for downstream data processing, comparison, interpretation, sharing and reuse. The few existing metadata management tools for genome-based studies provide weak curatorial frameworks for experimentalists to store and manage idiosyncratic, project-specific information, typically offering no automation supporting unified naming and numbering conventions for sequencing production environments that routinely deal with hundreds, if not thousands of samples at a time. Moreover, existing tools are not readily interfaced with bioinformatics executables, (e.g., BLAST, Bowtie2, custom pipelines). Our application, the Omics Metadata Management Software (OMMS), answers both needs, empowering experimentalists to generate intuitive, consistent metadata, and perform analyses and information management tasks via an intuitive web-based interface. Several use cases with short-read sequence datasets are provided to validate installation and integrated function, and suggest possible methodological road maps for prospective users. Provided examples highlight possible OMMS workflows for metadata curation, multistep analyses, and results management and downloading. The OMMS can be implemented as a stand alone-package for individual laboratories, or can be configured for webbased deployment supporting geographically-dispersed projects. The OMMS was developed using an open-source software base, is flexible, extensible and easily installed and executed. The OMMS can be obtained at http://omms.sandia.gov. Availability: The OMMS can be obtained at http://omms.sandia.gov.
Databáze:	MEDLINE
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