title: Scalable and cost-effective NGS genotyping in the cloud.
abstract: BACKGROUND
  While next-generation sequencing (NGS) costs have plummeted in recent years, cost and complexity of computation remain substantial barriers to the use of NGS in routine clinical care. The clinical potential of NGS will not be realized until robust and routine whole genome sequencing data can be accurately rendered to medically actionable reports within a time window of hours and at scales of economy in the 10's of dollars.
  
  
  RESULTS
  We take a step towards addressing this challenge, by using COSMOS, a cloud-enabled workflow management system, to develop GenomeKey, an NGS whole genome analysis workflow. COSMOS implements complex workflows making optimal use of high-performance compute clusters. Here we show that the Amazon Web Service (AWS) implementation of GenomeKey via COSMOS provides a fast, scalable, and cost-effective analysis of both public benchmarking and large-scale heterogeneous clinical NGS datasets.
  
  
  CONCLUSIONS
  Our systematic benchmarking reveals important new insights and considerations to produce clinical turn-around of whole genome analysis optimization and workflow management including strategic batching of individual genomes and efficient cluster resource configuration.
authors.affiliation: Department of Biomedical Informatics, Harvard Medical School 10 Shattuck Street, Boston, MA, 02115, USA. yassine_souilmi@hms.harvard.edu.|Department of Biology, Mohamed Vth University, 4 Ibn Battouta Avenue, B.P: 1014RP, Rabat, Morocco. yassine_souilmi@hms.harvard.edu.
authors.forename: Yassine
authors.initials: Y
authors.lastname: Souilmi
authors.affiliation: Department of Biomedical Informatics, Harvard Medical School 10 Shattuck Street, Boston, MA, 02115, USA. alex_lancaster@hms.harvard.edu.|Department of Pathology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, 02215, USA. alex_lancaster@hms.harvard.edu.
authors.forename: Alex K
authors.initials: AK
authors.lastname: Lancaster
authors.affiliation: Department of Biomedical Informatics, Harvard Medical School 10 Shattuck Street, Boston, MA, 02115, USA. jae-yoon_jung@hms.harvard.edu.
authors.forename: Jae-Yoon
authors.initials: JY
authors.lastname: Jung
authors.affiliation: Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 1, Pavia, 27100, Italy. ettore.rizzo@unipv.it.
authors.forename: Ettore
authors.initials: E
authors.lastname: Rizzo
authors.affiliation: Department of Biomedical Informatics, Harvard Medical School 10 Shattuck Street, Boston, MA, 02115, USA. jared_hawkins@hms.harvard.edu.
authors.forename: Jared B
authors.initials: JB
authors.lastname: Hawkins
authors.affiliation: Department of Biomedical Informatics, Harvard Medical School 10 Shattuck Street, Boston, MA, 02115, USA. rlpowles@vt.edu.
authors.forename: Ryan
authors.initials: R
authors.lastname: Powles
authors.affiliation: Department of Biology, Mohamed Vth University, 4 Ibn Battouta Avenue, B.P: 1014RP, Rabat, Morocco. amzazi@gmail.com.
authors.forename: Saaïd
authors.initials: S
authors.lastname: Amzazi
authors.affiliation: Department of Biology, Mohamed First University, Oujda, Nador, Morocco. hassan.ghazal@fulbrightmail.org.
authors.forename: Hassan
authors.initials: H
authors.lastname: Ghazal
authors.affiliation: Department of Biomedical Informatics, Harvard Medical School 10 Shattuck Street, Boston, MA, 02115, USA. peter_tonellato@hms.harvard.edu.|Department of Pathology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02215, USA. peter_tonellato@hms.harvard.edu.
authors.forename: Peter J
authors.initials: PJ
authors.lastname: Tonellato
authors.affiliation: Department of Pediatrics and Psychiatry (by courtesy), Division of Systems Medicine & Program in Biomedical Informatics, Stanford University, Stanford, CA, 94305, USA. dpwall@stanford.edu.
authors.forename: Dennis P
authors.initials: DP
authors.lastname: Wall
mesh_terms: D019985:Benchmarking; D000067917:Cloud Computing / Q000191:economics*; D003362:Cost-Benefit Analysis; D023281:Genomics; D060005:Genotyping Techniques / Q000191:economics*; D059014:High-Throughput Nucleotide Sequencing / Q000191:economics*; D006801:Humans