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dc.contributor.authorGafni, Eriken_US
dc.contributor.authorLuquette, Lovelace J.en_US
dc.contributor.authorLancaster, Alex K.en_US
dc.contributor.authorHawkins, Jared B.en_US
dc.contributor.authorJung, Jae-Yoonen_US
dc.contributor.authorSouilmi, Yassineen_US
dc.contributor.authorWall, Dennis P.en_US
dc.contributor.authorTonellato, Peter J.en_US
dc.date.accessioned2014-11-03T17:38:00Z
dc.date.issued2014en_US
dc.identifier.citationGafni, Erik, Lovelace J. Luquette, Alex K. Lancaster, Jared B. Hawkins, Jae-Yoon Jung, Yassine Souilmi, Dennis P. Wall, and Peter J. Tonellato. 2014. “COSMOS: Python library for massively parallel workflows.” Bioinformatics 30 (20): 2956-2958. doi:10.1093/bioinformatics/btu385. http://dx.doi.org/10.1093/bioinformatics/btu385.en
dc.identifier.issn1367-4803en
dc.identifier.urihttp://nrs.harvard.edu/urn-3:HUL.InstRepos:13347394
dc.description.abstractSummary: Efficient workflows to shepherd clinically generated genomic data through the multiple stages of a next-generation sequencing pipeline are of critical importance in translational biomedical science. Here we present COSMOS, a Python library for workflow management that allows formal description of pipelines and partitioning of jobs. In addition, it includes a user interface for tracking the progress of jobs, abstraction of the queuing system and fine-grained control over the workflow. Workflows can be created on traditional computing clusters as well as cloud-based services. Availability and implementation: Source code is available for academic non-commercial research purposes. Links to code and documentation are provided at http://lpm.hms.harvard.edu and http://wall-lab.stanford.edu. Contact: dpwall@stanford.edu or peter_tonellato@hms.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online.en
dc.language.isoen_USen
dc.publisherOxford University Pressen
dc.relation.isversionofdoi:10.1093/bioinformatics/btu385en
dc.relation.hasversionhttp://www.ncbi.nlm.nih.gov/pmc/articles/PMC4184253/pdf/en
dash.licenseLAAen_US
dc.titleCOSMOS: Python library for massively parallel workflowsen
dc.typeJournal Articleen_US
dc.description.versionVersion of Recorden
dc.relation.journalBioinformaticsen
dash.depositing.authorLuquette, Lovelace J.en_US
dc.date.available2014-11-03T17:38:00Z
dc.identifier.doi10.1093/bioinformatics/btu385*
dash.contributor.affiliatedSouilmi, Yassine
dash.contributor.affiliatedHawkins, Jared
dash.contributor.affiliatedLuquette, Joe
dash.contributor.affiliatedTonellato, Peter


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