An analytical framework for optimizing variant discovery from personal genomes

The standardization and performance testing of analysis tools is a prerequisite to widespread adoption of genome-wide sequencing, particularly in the clinic. However, performance testing is currently complicated by the paucity of standards and comparison metrics, as well as by the heterogeneity in s...

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Autores principales: Highnam, Gareth, Wang, Jason J., Kusler, Dean, Zook, Justin, Vijayan, Vinaya, Leibovich, Nir, Mittelman, David
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Pub. Group 2015
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4351570/
https://www.ncbi.nlm.nih.gov/pubmed/25711446
http://dx.doi.org/10.1038/ncomms7275
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author Highnam, Gareth
Wang, Jason J.
Kusler, Dean
Zook, Justin
Vijayan, Vinaya
Leibovich, Nir
Mittelman, David
author_facet Highnam, Gareth
Wang, Jason J.
Kusler, Dean
Zook, Justin
Vijayan, Vinaya
Leibovich, Nir
Mittelman, David
author_sort Highnam, Gareth
collection PubMed
description The standardization and performance testing of analysis tools is a prerequisite to widespread adoption of genome-wide sequencing, particularly in the clinic. However, performance testing is currently complicated by the paucity of standards and comparison metrics, as well as by the heterogeneity in sequencing platforms, applications and protocols. Here we present the genome comparison and analytic testing (GCAT) platform to facilitate development of performance metrics and comparisons of analysis tools across these metrics. Performance is reported through interactive visualizations of benchmark and performance testing data, with support for data slicing and filtering. The platform is freely accessible at http://www.bioplanet.com/gcat.
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spelling pubmed-43515702015-03-19 An analytical framework for optimizing variant discovery from personal genomes Highnam, Gareth Wang, Jason J. Kusler, Dean Zook, Justin Vijayan, Vinaya Leibovich, Nir Mittelman, David Nat Commun Article The standardization and performance testing of analysis tools is a prerequisite to widespread adoption of genome-wide sequencing, particularly in the clinic. However, performance testing is currently complicated by the paucity of standards and comparison metrics, as well as by the heterogeneity in sequencing platforms, applications and protocols. Here we present the genome comparison and analytic testing (GCAT) platform to facilitate development of performance metrics and comparisons of analysis tools across these metrics. Performance is reported through interactive visualizations of benchmark and performance testing data, with support for data slicing and filtering. The platform is freely accessible at http://www.bioplanet.com/gcat. Nature Pub. Group 2015-02-25 /pmc/articles/PMC4351570/ /pubmed/25711446 http://dx.doi.org/10.1038/ncomms7275 Text en Copyright © 2015, Nature Publishing Group, a division of Macmillan Publishers Limited. All Rights Reserved. http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Highnam, Gareth
Wang, Jason J.
Kusler, Dean
Zook, Justin
Vijayan, Vinaya
Leibovich, Nir
Mittelman, David
An analytical framework for optimizing variant discovery from personal genomes
title An analytical framework for optimizing variant discovery from personal genomes
title_full An analytical framework for optimizing variant discovery from personal genomes
title_fullStr An analytical framework for optimizing variant discovery from personal genomes
title_full_unstemmed An analytical framework for optimizing variant discovery from personal genomes
title_short An analytical framework for optimizing variant discovery from personal genomes
title_sort analytical framework for optimizing variant discovery from personal genomes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4351570/
https://www.ncbi.nlm.nih.gov/pubmed/25711446
http://dx.doi.org/10.1038/ncomms7275
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