The NIH BD2K center for big data in translational genomics

Author:

Paten Benedict1,Diekhans Mark1,Druker Brian J2,Friend Stephen3,Guinney Justin3,Gassner Nadine1,Guttman Mitchell4,James Kent W1,Mantey Patrick15,Margolin Adam A6,Massie Matt7,Novak Adam M1,Nothaft Frank7,Pachter Lior89,Patterson David7,Smuga-Otto Maciej1,Stuart Joshua M1,Van’t Veer Laura10,Wold Barbara4,Haussler David111

Affiliation:

1. UC Santa Cruz Genomics Institute, University of California, Santa Cruz, CA, USA

2. Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA

3. Sage Bionetworks, Fairview Ave North, Seattle 98109, WA, USA

4. Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA

5. Jack Baskin School of Engineering, University of California, Santa Cruz, CA, USA

6. Computational Biology Program, Oregon Health & Science University, Portland, OR, USA

7. Department of Electrical Engineering and Computer Science, University of California, Berkeley, CA, USA

8. Department of Mathematics, University of California Berkeley, Berkeley, CA, USA

9. Department of Molecular & Cellular Biology, University of California Berkeley, Berkeley, CA, USA

10. Department of Laboratory Medicine, University of California, San Francisco, CA, USA

11. Howard Hughes Medical Institute, Bethesda, MD, USA

Abstract

Abstract The world’s genomics data will never be stored in a single repository – rather, it will be distributed among many sites in many countries. No one site will have enough data to explain genotype to phenotype relationships in rare diseases; therefore, sites must share data. To accomplish this, the genetics community must forge common standards and protocols to make sharing and computing data among many sites a seamless activity. Through the Global Alliance for Genomics and Health, we are pioneering the development of shared application programming interfaces (APIs) to connect the world’s genome repositories. In parallel, we are developing an open source software stack (ADAM) that uses these APIs. This combination will create a cohesive genome informatics ecosystem. Using containers, we are facilitating the deployment of this software in a diverse array of environments. Through benchmarking efforts and big data driver projects, we are ensuring ADAM’s performance and utility.

Publisher

Oxford University Press (OUP)

Subject

Health Informatics

Reference14 articles.

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