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geck: trio-based comparative benchmarking of variant calls
MOTIVATION: Classical methods of comparing the accuracies of variant calling pipelines are based on truth sets of variants whose genotypes are previously determined with high confidence. An alternative way of performing benchmarking is based on Mendelian constraints between related individuals. Stat...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6184596/ https://www.ncbi.nlm.nih.gov/pubmed/29850774 http://dx.doi.org/10.1093/bioinformatics/bty415 |
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author | Kómár, Péter Kural, Deniz |
author_facet | Kómár, Péter Kural, Deniz |
author_sort | Kómár, Péter |
collection | PubMed |
description | MOTIVATION: Classical methods of comparing the accuracies of variant calling pipelines are based on truth sets of variants whose genotypes are previously determined with high confidence. An alternative way of performing benchmarking is based on Mendelian constraints between related individuals. Statistical analysis of Mendelian violations can provide truth set-independent benchmarking information, and enable benchmarking less-studied variants and diverse populations. RESULTS: We introduce a statistical mixture model for comparing two variant calling pipelines from genotype data they produce after running on individual members of a trio. We determine the accuracy of our model by comparing the precision and recall of GATK Unified Genotyper and Haplotype Caller on the high-confidence SNPs of the NIST Ashkenazim trio and the two independent Platinum Genome trios. We show that our method is able to estimate differential precision and recall between the two pipelines with [Formula: see text] uncertainty. AVAILABILITY AND IMPLEMENTATION: The Python library geck, and usage examples are available at the following URL: https://github.com/sbg/geck, under the GNU General Public License v3. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-6184596 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-61845962018-10-18 geck: trio-based comparative benchmarking of variant calls Kómár, Péter Kural, Deniz Bioinformatics Original Papers MOTIVATION: Classical methods of comparing the accuracies of variant calling pipelines are based on truth sets of variants whose genotypes are previously determined with high confidence. An alternative way of performing benchmarking is based on Mendelian constraints between related individuals. Statistical analysis of Mendelian violations can provide truth set-independent benchmarking information, and enable benchmarking less-studied variants and diverse populations. RESULTS: We introduce a statistical mixture model for comparing two variant calling pipelines from genotype data they produce after running on individual members of a trio. We determine the accuracy of our model by comparing the precision and recall of GATK Unified Genotyper and Haplotype Caller on the high-confidence SNPs of the NIST Ashkenazim trio and the two independent Platinum Genome trios. We show that our method is able to estimate differential precision and recall between the two pipelines with [Formula: see text] uncertainty. AVAILABILITY AND IMPLEMENTATION: The Python library geck, and usage examples are available at the following URL: https://github.com/sbg/geck, under the GNU General Public License v3. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2018-10-15 2018-05-29 /pmc/articles/PMC6184596/ /pubmed/29850774 http://dx.doi.org/10.1093/bioinformatics/bty415 Text en © The Author(s) 2018. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Original Papers Kómár, Péter Kural, Deniz geck: trio-based comparative benchmarking of variant calls |
title |
geck: trio-based comparative benchmarking of variant calls |
title_full |
geck: trio-based comparative benchmarking of variant calls |
title_fullStr |
geck: trio-based comparative benchmarking of variant calls |
title_full_unstemmed |
geck: trio-based comparative benchmarking of variant calls |
title_short |
geck: trio-based comparative benchmarking of variant calls |
title_sort | geck: trio-based comparative benchmarking of variant calls |
topic | Original Papers |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6184596/ https://www.ncbi.nlm.nih.gov/pubmed/29850774 http://dx.doi.org/10.1093/bioinformatics/bty415 |
work_keys_str_mv | AT komarpeter gecktriobasedcomparativebenchmarkingofvariantcalls AT kuraldeniz gecktriobasedcomparativebenchmarkingofvariantcalls |