Journal:Launching genomics into the cloud: Deployment of Mercury, a next generation sequence analysis pipeline
| Full article title | Launching genomics into the cloud: Deployment of Mercury, a next generation sequence analysis pipeline |
|---|---|
| Journal | BMC Bioinformatics |
| Author(s) |
Reid, Jeffrey G.; Carroll, Andrew; Veeraraghavan, Narayanan; Dahdouli, Mahmoud; Sundquist, Andreas; English, Adam; Bainbridge, Matthew; White, Simon; Salerno, William; Buhay, Christian; Yu, Fuli; Muzny, Donna; Daly, Richard; Duyk, Geoff; Gibbs, Richard A. Boerwinkle, Eric |
| Author affiliation(s) | Baylor College of Medicine; DNAnexus |
| Primary contact | Email: jgreid@bcm.edu |
| Year published | 2014 |
| Volume and issue | 15 |
| Page(s) | 30 |
| DOI | [10.1186/1471-2105-15-30 10.1186/1471-2105-15-30] |
| ISSN | 1471-2105 |
| Distribution license | Creative Commons Attribution 2.0 Generic |
| Website | http://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-30 |
| Download | http://bmcbioinformatics.biomedcentral.com/track/pdf/10.1186/1471-2105-15-30 (PDF) |
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Abstract
Background: Massively parallel DNA sequencing generates staggering amounts of data. Decreasing cost, increasing throughput, and improved annotation have expanded the diversity of genomics applications in research and clinical practice. This expanding scale creates analytical challenges: accommodating peak compute demand, coordinating secure access for multiple analysts, and sharing validated tools and results.
Results: To address these challenges, we have developed the Mercury analysis pipeline and deployed it in local hardware and the Amazon Web Services cloud via the DNAnexus platform. Mercury is an automated, flexible, and extensible analysis workflow that provides accurate and reproducible genomic results at scales ranging from individuals to large cohorts.
Conclusions: By taking advantage of cloud computing and with Mercury implemented on the DNAnexus platform, we have demonstrated a powerful combination of a robust and fully validated software pipeline and a scalable computational resource that, to date, we have applied to more than 10,000 whole genome and whole exome samples.
Keywords: NGS data, Variant calling, Annotation, Clinical sequencing, Cloud computing
References
Notes
This presentation is faithful to the original, with only a few minor changes to presentation. In some cases important information was missing from the references, and that information was added.
