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A general framework for estimating the relative pathogenicity of human genetic variants
- Martin Kircher ORCID:orcid.org/0000-0001-9278-54711 na1,
- Daniela M Witten2 na1,
- Preti Jain3 nAff4,
- Brian J O'Roak1 nAff4,
- Gregory M Cooper ORCID:orcid.org/0000-0001-5509-99233 &
- …
- Jay Shendure1
Nature Geneticsvolume 46, pages310–315 (2014)Cite this article
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Abstract
Current methods for annotating and interpreting human genetic variation tend to exploit a single information type (for example, conservation) and/or are restricted in scope (for example, to missense changes). Here we describe Combined Annotation–Dependent Depletion (CADD), a method for objectively integrating many diverse annotations into a single measure (C score) for each variant. We implement CADD as a support vector machine trained to differentiate 14.7 million high-frequency human-derived alleles from 14.7 million simulated variants. We precompute C scores for all 8.6 billion possible human single-nucleotide variants and enable scoring of short insertions-deletions. C scores correlate with allelic diversity, annotations of functionality, pathogenicity, disease severity, experimentally measured regulatory effects and complex trait associations, and they highly rank known pathogenic variants within individual genomes. The ability of CADD to prioritize functional, deleterious and pathogenic variants across many functional categories, effect sizes and genetic architectures is unmatched by any current single-annotation method.
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Acknowledgements
We thank P. Green and members of the Shendure laboratory for helpful discussions and suggestions. Our work was supported by US NIH grants U54HG006493 (to J.S. and G.M.C.), DP5OD009145 (to D.M.W.) and DP1HG007811 (to J.S.).
Author information
Preti Jain & Brian J O'Roak
Present address: Present address: Department of Molecular and Medical Genetics, Oregon Health and Science University, Portland, Oregon, USA.,
Martin Kircher and Daniela M Witten: These authors contributed equally to this work.
Authors and Affiliations
Department of Genome Sciences, University of Washington, Seattle, Washington, USA
Martin Kircher, Brian J O'Roak & Jay Shendure
Department of Biostatistics, University of Washington, Seattle, Washington, USA
Daniela M Witten
HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
Preti Jain & Gregory M Cooper
- Martin Kircher
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- Preti Jain
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- Brian J O'Roak
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- Gregory M Cooper
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- Jay Shendure
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Contributions
G.M.C. and J.S. designed the study. M.K. processed the annotation data and scores and developed and implemented the simulator and scripts required for scoring. P.J. and B.J.O. prepared and provided data sets and annotations. D.M.W. and M.K. developed the model and performed model training. D.M.W. performed the analysis of individual features and interactions. M.K., D.M.W., G.M.C. and J.S. analyzed the model's performance on different data sets. G.M.C. analyzed the GWAS data. J.S., G.M.C., M.K. and D.M.W. wrote the manuscript with input from all authors.
Corresponding authors
Correspondence toGregory M Cooper orJay Shendure.
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Competing interests
The authors (M.K., D.M.W., G.M.C. and J.S.) have filed a provisional patent application with the US Patent and Trademark Office on the basis of CADD.
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Supplementary Figures 1–18, Supplementary Tables 1–12 and Supplementary Note (PDF 4022 kb)
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Kircher, M., Witten, D., Jain, P.et al. A general framework for estimating the relative pathogenicity of human genetic variants.Nat Genet46, 310–315 (2014). https://doi.org/10.1038/ng.2892
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