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Effective variant filtering and expected candidate variant yield in studies of rare human disease
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...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282602/ https://www.ncbi.nlm.nih.gov/pubmed/34267211 http://dx.doi.org/10.1038/s41525-021-00227-3 |
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author | Pedersen, Brent S. Brown, Joe M. Dashnow, Harriet Wallace, Amelia D. Velinder, Matt Tristani-Firouzi, Martin Schiffman, Joshua D. Tvrdik, Tatiana Mao, Rong Best, D. Hunter Bayrak-Toydemir, Pinar Quinlan, Aaron R. |
author_facet | Pedersen, Brent S. Brown, Joe M. Dashnow, Harriet Wallace, Amelia D. Velinder, Matt Tristani-Firouzi, Martin Schiffman, Joshua D. Tvrdik, Tatiana Mao, Rong Best, D. Hunter Bayrak-Toydemir, Pinar Quinlan, Aaron R. |
author_sort | Pedersen, Brent S. |
collection | PubMed |
description | 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 explore effective guidelines for variant (SNP and INDEL) filtering and report the expected number of candidates for de novo dominant, recessive, and autosomal dominant modes of inheritance. We derived these guidelines using two large family-based cohorts that underwent whole-genome sequencing, as well as two family cohorts with whole-exome sequencing. The filters are applied to common attributes, including genotype-quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield ~10 candidate SNP and INDEL variants per exome, and 18 per genome for recessive and de novo dominant modes of inheritance, with substantially more candidates for autosomal dominant inheritance. For family-based, whole-genome sequencing studies, this number includes an average of three de novo, ten compound heterozygous, 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. |
format | Online Article Text |
id | pubmed-8282602 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-82826022021-07-23 Effective variant filtering and expected candidate variant yield in studies of rare human disease Pedersen, Brent S. Brown, Joe M. Dashnow, Harriet Wallace, Amelia D. Velinder, Matt Tristani-Firouzi, Martin Schiffman, Joshua D. Tvrdik, Tatiana Mao, Rong Best, D. Hunter Bayrak-Toydemir, Pinar Quinlan, Aaron R. NPJ Genom Med Article 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 explore effective guidelines for variant (SNP and INDEL) filtering and report the expected number of candidates for de novo dominant, recessive, and autosomal dominant modes of inheritance. We derived these guidelines using two large family-based cohorts that underwent whole-genome sequencing, as well as two family cohorts with whole-exome sequencing. The filters are applied to common attributes, including genotype-quality, sequencing depth, allele balance, and population allele frequency. The resulting guidelines yield ~10 candidate SNP and INDEL variants per exome, and 18 per genome for recessive and de novo dominant modes of inheritance, with substantially more candidates for autosomal dominant inheritance. For family-based, whole-genome sequencing studies, this number includes an average of three de novo, ten compound heterozygous, 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. Nature Publishing Group UK 2021-07-15 /pmc/articles/PMC8282602/ /pubmed/34267211 http://dx.doi.org/10.1038/s41525-021-00227-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Pedersen, Brent S. Brown, Joe M. Dashnow, Harriet Wallace, Amelia D. Velinder, Matt Tristani-Firouzi, Martin Schiffman, Joshua D. Tvrdik, Tatiana Mao, Rong Best, D. Hunter Bayrak-Toydemir, Pinar Quinlan, Aaron R. Effective variant filtering and expected candidate variant yield in studies of rare human disease |
title | Effective variant filtering and expected candidate variant yield in studies of rare human disease |
title_full | Effective variant filtering and expected candidate variant yield in studies of rare human disease |
title_fullStr | Effective variant filtering and expected candidate variant yield in studies of rare human disease |
title_full_unstemmed | Effective variant filtering and expected candidate variant yield in studies of rare human disease |
title_short | Effective variant filtering and expected candidate variant yield in studies of rare human disease |
title_sort | effective variant filtering and expected candidate variant yield in studies of rare human disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8282602/ https://www.ncbi.nlm.nih.gov/pubmed/34267211 http://dx.doi.org/10.1038/s41525-021-00227-3 |
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