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 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.
CITATION STYLE
Gafni, E., Luquette, L. J., Lancaster, A. K., Hawkins, J. B., Jung, J. Y., Souilmi, Y., … Tonellato, P. J. (2014). COSMOS: Python library for massively parallel workflows. Bioinformatics (Oxford, England), 30(20), 2956–2958. https://doi.org/10.1093/bioinformatics/btu385
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