Aether: leveraging linear programming for optimal cloud computing in genomics.
other · Level V
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- Record sourced from PubMed, PMID 29228186.
- Also identified by DOI 10.1093/bioinformatics/btx787 and PMC identifier 5925767.
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Abstract
Across biology, we are seeing rapid developments in scale of data production without a corresponding increase in data analysis capabilities. Here, we present Aether (http://aether.kosticlab.org), an intuitive, easy-to-use, cost-effective and scalable framework that uses linear programming to optimally bid on and deploy combinations of underutilized cloud computing resources. Our approach simultaneously minimizes the cost of data analysis and provides an easy transition from users' existing HPC pipelines. Data utilized are available at https://pubs.broadinstitute.org/diabimmune and with EBI SRA accession ERP005989. Source code is available at (https://github.com/kosticlab/aether). Examples, documentation and a tutorial are available at http://aether.kosticlab.org. chirag_patel@hms.harvard.edu or aleksandar.kostic@joslin.harvard.edu. Supplementary data are available at Bioinformatics online.
Medical subject headings
- Cloud Computing
- Genomics
- Programming, Linear
- Software