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History
- September 2, 2016.
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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Author Information
- Nicola Whiffin1 (n.whiffin{at}csc.mrc.ac.uk),
- Eric Minikel2 (eminikel{at}broadinstitute.org),
- Roddy Walsh1 (r.walsh{at}imperial.ac.uk),
- Anne O'Donnell-Luria2 (anne.odonnell{at}childrens.harvard.edu),
- Konrad Karczewski3 (konradk{at}broadinstitute.org),
- Alexander Y Ing4 (aing{at}partners.org),
- Paul J R Barton1 (p.barton{at}imperial.ac.uk) (http://www.imperial.ac.uk/people/p.barton),
- Birgit Funke4 (bfunke{at}partners.org),
- Stuart A Cook1 (stuart.cook{at}csc.mrc.ac.uk),
- Daniel G MacArthur5 (macarthur{at}atgu.mgh.harvard.edu) and
- James S Ware1,6 (j.ware{at}imperial.ac.uk)
- 1 Imperial College London;
- 2 Broad Institute of MIT and Harvard;
- 3 Analytic and Translational Genetics Unit;
- 4 Laboratory for Molecular Medicine;
- 5 Massachusetts General Hospital
- ↵* Corresponding author; email: j.ware{at}imperial.ac.uk
- Posted September 2, 2016.
Using high-resolution variant frequencies to empower clinical genome interpretation
