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Best practices for evaluating single nucleotide variant calling methods for microbial genomics
Innovations in sequencing technologies have allowed biologists to make incredible advances in understanding biological systems. As experience grows, researchers increasingly recognize that analyzing the wealth of data provided by these new sequencing platforms requires careful attention to detail fo...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4493402/ https://www.ncbi.nlm.nih.gov/pubmed/26217378 http://dx.doi.org/10.3389/fgene.2015.00235 |
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author | Olson, Nathan D. Lund, Steven P. Colman, Rebecca E. Foster, Jeffrey T. Sahl, Jason W. Schupp, James M. Keim, Paul Morrow, Jayne B. Salit, Marc L. Zook, Justin M. |
author_facet | Olson, Nathan D. Lund, Steven P. Colman, Rebecca E. Foster, Jeffrey T. Sahl, Jason W. Schupp, James M. Keim, Paul Morrow, Jayne B. Salit, Marc L. Zook, Justin M. |
author_sort | Olson, Nathan D. |
collection | PubMed |
description | Innovations in sequencing technologies have allowed biologists to make incredible advances in understanding biological systems. As experience grows, researchers increasingly recognize that analyzing the wealth of data provided by these new sequencing platforms requires careful attention to detail for robust results. Thus far, much of the scientific Communit’s focus for use in bacterial genomics has been on evaluating genome assembly algorithms and rigorously validating assembly program performance. Missing, however, is a focus on critical evaluation of variant callers for these genomes. Variant calling is essential for comparative genomics as it yields insights into nucleotide-level organismal differences. Variant calling is a multistep process with a host of potential error sources that may lead to incorrect variant calls. Identifying and resolving these incorrect calls is critical for bacterial genomics to advance. The goal of this review is to provide guidance on validating algorithms and pipelines used in variant calling for bacterial genomics. First, we will provide an overview of the variant calling procedures and the potential sources of error associated with the methods. We will then identify appropriate datasets for use in evaluating algorithms and describe statistical methods for evaluating algorithm performance. As variant calling moves from basic research to the applied setting, standardized methods for performance evaluation and reporting are required; it is our hope that this review provides the groundwork for the development of these standards. |
format | Online Article Text |
id | pubmed-4493402 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-44934022015-07-27 Best practices for evaluating single nucleotide variant calling methods for microbial genomics Olson, Nathan D. Lund, Steven P. Colman, Rebecca E. Foster, Jeffrey T. Sahl, Jason W. Schupp, James M. Keim, Paul Morrow, Jayne B. Salit, Marc L. Zook, Justin M. Front Genet Genetics Innovations in sequencing technologies have allowed biologists to make incredible advances in understanding biological systems. As experience grows, researchers increasingly recognize that analyzing the wealth of data provided by these new sequencing platforms requires careful attention to detail for robust results. Thus far, much of the scientific Communit’s focus for use in bacterial genomics has been on evaluating genome assembly algorithms and rigorously validating assembly program performance. Missing, however, is a focus on critical evaluation of variant callers for these genomes. Variant calling is essential for comparative genomics as it yields insights into nucleotide-level organismal differences. Variant calling is a multistep process with a host of potential error sources that may lead to incorrect variant calls. Identifying and resolving these incorrect calls is critical for bacterial genomics to advance. The goal of this review is to provide guidance on validating algorithms and pipelines used in variant calling for bacterial genomics. First, we will provide an overview of the variant calling procedures and the potential sources of error associated with the methods. We will then identify appropriate datasets for use in evaluating algorithms and describe statistical methods for evaluating algorithm performance. As variant calling moves from basic research to the applied setting, standardized methods for performance evaluation and reporting are required; it is our hope that this review provides the groundwork for the development of these standards. Frontiers Media S.A. 2015-07-07 /pmc/articles/PMC4493402/ /pubmed/26217378 http://dx.doi.org/10.3389/fgene.2015.00235 Text en Copyright © 2015 Olson, Lund, Colman, Foster, Sahl, Schupp, Keim, Morrow, Salit and Zook. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Olson, Nathan D. Lund, Steven P. Colman, Rebecca E. Foster, Jeffrey T. Sahl, Jason W. Schupp, James M. Keim, Paul Morrow, Jayne B. Salit, Marc L. Zook, Justin M. Best practices for evaluating single nucleotide variant calling methods for microbial genomics |
title | Best practices for evaluating single nucleotide variant calling methods for microbial genomics |
title_full | Best practices for evaluating single nucleotide variant calling methods for microbial genomics |
title_fullStr | Best practices for evaluating single nucleotide variant calling methods for microbial genomics |
title_full_unstemmed | Best practices for evaluating single nucleotide variant calling methods for microbial genomics |
title_short | Best practices for evaluating single nucleotide variant calling methods for microbial genomics |
title_sort | best practices for evaluating single nucleotide variant calling methods for microbial genomics |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4493402/ https://www.ncbi.nlm.nih.gov/pubmed/26217378 http://dx.doi.org/10.3389/fgene.2015.00235 |
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