Scaling accurate genetic variant discovery to tens of thousands of samples
Mark A. DePristo,
Tim J. Fennell,
Mauricio O. Carneiro,
Geraldine A. Van der Auwera,
David E. Kling,
Laura D Gauthier,
Mark J. Daly,
Daniel G MacArthur,
Posted 14 Nov 2017
bioRxiv DOI: 10.1101/201178
Posted 14 Nov 2017
Comprehensive disease gene discovery in both common and rare diseases will require the efficient and accurate detection of all classes of genetic variation across tens to hundreds of thousands of human samples. We describe here a novel assembly-based approach to variant calling, the GATK HaplotypeCaller (HC) and Reference Confidence Model (RCM), that determines genotype likelihoods independently per-sample but performs joint calling across all samples within a project simultaneously. We show by calling over 90,000 samples from the Exome Aggregation Consortium (ExAC) that, in contrast to other algorithms, the HC-RCM scales efficiently to very large sample sizes without loss in accuracy; and that the accuracy of indel variant calling is superior in comparison to other algorithms. More importantly, the HC-RCM produces a fully squared-off matrix of genotypes across all samples at every genomic position being investigated. The HC- RCM is a novel, scalable, assembly-based algorithm with abundant applications for population genetics and clinical studies.
- Downloaded 7,927 times
- Download rankings, all-time:
- Site-wide: 1,079
- In genomics: 100
- Year to date:
- Site-wide: 1,576
- Since beginning of last month:
- Site-wide: 1,692
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!