COSMOS: Python library for massively parallel workflows

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COSMOS: Python library for massively parallel workflows

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Title: COSMOS: Python library for massively parallel workflows
Author: Gafni, Erik; Luquette, Lovelace J.; Lancaster, Alex K.; Hawkins, Jared B.; Jung, Jae-Yoon; Souilmi, Yassine; Wall, Dennis P.; Tonellato, Peter J.

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Citation: Gafni, 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.
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Abstract: Summary: 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 and Contact: or Supplementary information: Supplementary data are available at Bioinformatics online.
Published Version: doi:10.1093/bioinformatics/btu385
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