Nature Communications (Oct 2018)
Functional equivalence of genome sequencing analysis pipelines enables harmonized variant calling across human genetics projects
- Allison A. Regier,
- Yossi Farjoun,
- David E. Larson,
- Olga Krasheninina,
- Hyun Min Kang,
- Daniel P. Howrigan,
- Bo-Juen Chen,
- Manisha Kher,
- Eric Banks,
- Darren C. Ames,
- Adam C. English,
- Heng Li,
- Jinchuan Xing,
- Yeting Zhang,
- Tara Matise,
- Goncalo R. Abecasis,
- Will Salerno,
- Michael C. Zody,
- Benjamin M. Neale,
- Ira M. Hall
Affiliations
- Allison A. Regier
- McDonnell Genome Institute, Washington University School of Medicine
- Yossi Farjoun
- Broad Institute of MIT and Harvard
- David E. Larson
- McDonnell Genome Institute, Washington University School of Medicine
- Olga Krasheninina
- Human Genome Sequencing Center, Baylor College of Medicine
- Hyun Min Kang
- Department of Biostatistics, University of Michigan
- Daniel P. Howrigan
- Broad Institute of MIT and Harvard
- Bo-Juen Chen
- New York Genome Center
- Manisha Kher
- New York Genome Center
- Eric Banks
- Broad Institute of MIT and Harvard
- Darren C. Ames
- DNAnexus Inc
- Adam C. English
- Spiral Genetics
- Heng Li
- Broad Institute of MIT and Harvard
- Jinchuan Xing
- Department of Genetics, Rutgers University
- Yeting Zhang
- Department of Genetics, Rutgers University
- Tara Matise
- Department of Genetics, Rutgers University
- Goncalo R. Abecasis
- Department of Biostatistics, University of Michigan
- Will Salerno
- Human Genome Sequencing Center, Baylor College of Medicine
- Michael C. Zody
- New York Genome Center
- Benjamin M. Neale
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard
- Ira M. Hall
- McDonnell Genome Institute, Washington University School of Medicine
- DOI
- https://doi.org/10.1038/s41467-018-06159-4
- Journal volume & issue
-
Vol. 9,
no. 1
pp. 1 – 8
Abstract
Sharing of whole genome sequencing (WGS) data improves study scale and power, but data from different groups are often incompatible. Here, US genome centers and NIH programs define WGS data processing standards and a flexible validation method, facilitating collaboration in human genetics research.
