geck: trio-based comparative benchmarking of variant calls

geck: trio-based comparative benchmarking of variant calls Abstract 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 10–3 uncertainty. Availability 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. Contact peter.komar@totient.bio Supplementary information Supplementary materials are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press. 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 http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Bioinformatics Oxford University Press

geck: trio-based comparative benchmarking of variant calls

Bioinformatics , Volume Advance Article – May 29, 2018

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Publisher
Oxford University Press
Copyright
© The Author(s) 2018. Published by Oxford University Press.
ISSN
1367-4803
eISSN
1460-2059
D.O.I.
10.1093/bioinformatics/bty415
Publisher site
See Article on Publisher Site

Abstract

Abstract 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 10–3 uncertainty. Availability 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. Contact peter.komar@totient.bio Supplementary information Supplementary materials are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press. 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

Journal

BioinformaticsOxford University Press

Published: May 29, 2018

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