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Effective variant filtering and expected candidate variant yield in studies of rare human disease

View ORCID ProfileBrent S. Pedersen, View ORCID ProfileJoe M. Brown, View ORCID ProfileHarriet Dashnow, Amelia D. Wallace, View ORCID ProfileMatt Velinder, Tatiana Tvrdik, Rong Mao, View ORCID ProfileD. Hunter Best, View ORCID ProfilePinar Bayrak-Toydemir, View ORCID ProfileAaron R. Quinlan
doi: https://doi.org/10.1101/2020.08.13.249532
Brent S. Pedersen
1Department of Human Genetics, University of Utah, Salt Lake City, Utah, USA
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Joe M. Brown
1Department of Human Genetics, University of Utah, Salt Lake City, Utah, USA
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Harriet Dashnow
1Department of Human Genetics, University of Utah, Salt Lake City, Utah, USA
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Amelia D. Wallace
1Department of Human Genetics, University of Utah, Salt Lake City, Utah, USA
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Matt Velinder
1Department of Human Genetics, University of Utah, Salt Lake City, Utah, USA
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Tatiana Tvrdik
4Department of Pathology, University of Utah, Salt Lake City, Utah, USA
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Rong Mao
4Department of Pathology, University of Utah, Salt Lake City, Utah, USA
6ARUP Institute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah, USA
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D. Hunter Best
4Department of Pathology, University of Utah, Salt Lake City, Utah, USA
5Department of Pediatrics, University of Utah, Salt Lake City, Utah, USA
6ARUP Institute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah, USA
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Pinar Bayrak-Toydemir
4Department of Pathology, University of Utah, Salt Lake City, Utah, USA
6ARUP Institute for Clinical and Experimental Pathology, ARUP Laboratories, Salt Lake City, Utah, USA
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Aaron R. Quinlan
1Department of Human Genetics, University of Utah, Salt Lake City, Utah, USA
2Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA
3Utah Center for Genetic Discovery, University of Utah, Salt Lake City, Utah, USA
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  • For correspondence: aaronquinlan@gmail.com
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ABSTRACT

In studies of families with rare disease, it is common to screen for de novo mutations, as well as recessive or dominant variants that explain the phenotype. However, the filtering strategies and software used to prioritize high-confidence variants vary from study to study. In an effort to establish recommendations for rare disease research, we derive effective guidelines for variant filtering and report the expected number of candidates for de novo dominant and recessive modes of inheritance. The filters are applied to common attributes, including genotype quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield approximately 10 candidate SNP and INDEL variants per exome, and 18 per genome. For whole genomes, this includes an average of three de novo, ten compound-heterozygotes, one autosomal recessive, four X-linked variants, and roughly 100 candidate variants following autosomal dominant inheritance. The slivar software we developed to establish and rapidly apply these filters to VCF files is available at https://github.com/brentp/slivar under an MIT license, and includes documentation and recommendations for best practices for rare disease analysis.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • Fix author initials and naming

Copyright 
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 4.0 International license.
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Posted August 14, 2020.
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Effective variant filtering and expected candidate variant yield in studies of rare human disease
Brent S. Pedersen, Joe M. Brown, Harriet Dashnow, Amelia D. Wallace, Matt Velinder, Tatiana Tvrdik, Rong Mao, D. Hunter Best, Pinar Bayrak-Toydemir, Aaron R. Quinlan
bioRxiv 2020.08.13.249532; doi: https://doi.org/10.1101/2020.08.13.249532
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Effective variant filtering and expected candidate variant yield in studies of rare human disease
Brent S. Pedersen, Joe M. Brown, Harriet Dashnow, Amelia D. Wallace, Matt Velinder, Tatiana Tvrdik, Rong Mao, D. Hunter Best, Pinar Bayrak-Toydemir, Aaron R. Quinlan
bioRxiv 2020.08.13.249532; doi: https://doi.org/10.1101/2020.08.13.249532

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