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RESCRIPt: Reproducible sequence taxonomy reference database management
Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleoti...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8601625/ https://www.ncbi.nlm.nih.gov/pubmed/34748542 http://dx.doi.org/10.1371/journal.pcbi.1009581 |
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author | Robeson, Michael S. O’Rourke, Devon R. Kaehler, Benjamin D. Ziemski, Michal Dillon, Matthew R. Foster, Jeffrey T. Bokulich, Nicholas A. |
author_facet | Robeson, Michael S. O’Rourke, Devon R. Kaehler, Benjamin D. Ziemski, Michal Dillon, Matthew R. Foster, Jeffrey T. Bokulich, Nicholas A. |
author_sort | Robeson, Michael S. |
collection | PubMed |
description | Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardization limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a Python 3 software package and QIIME 2 plugin for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. To highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. RESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt. |
format | Online Article Text |
id | pubmed-8601625 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-86016252021-11-19 RESCRIPt: Reproducible sequence taxonomy reference database management Robeson, Michael S. O’Rourke, Devon R. Kaehler, Benjamin D. Ziemski, Michal Dillon, Matthew R. Foster, Jeffrey T. Bokulich, Nicholas A. PLoS Comput Biol Research Article Nucleotide sequence and taxonomy reference databases are critical resources for widespread applications including marker-gene and metagenome sequencing for microbiome analysis, diet metabarcoding, and environmental DNA (eDNA) surveys. Reproducibly generating, managing, using, and evaluating nucleotide sequence and taxonomy reference databases creates a significant bottleneck for researchers aiming to generate custom sequence databases. Furthermore, database composition drastically influences results, and lack of standardization limits cross-study comparisons. To address these challenges, we developed RESCRIPt, a Python 3 software package and QIIME 2 plugin for reproducible generation and management of reference sequence taxonomy databases, including dedicated functions that streamline creating databases from popular sources, and functions for evaluating, comparing, and interactively exploring qualitative and quantitative characteristics across reference databases. To highlight the breadth and capabilities of RESCRIPt, we provide several examples for working with popular databases for microbiome profiling (SILVA, Greengenes, NCBI-RefSeq, GTDB), eDNA and diet metabarcoding surveys (BOLD, GenBank), as well as for genome comparison. We show that bigger is not always better, and reference databases with standardized taxonomies and those that focus on type strains have quantitative advantages, though may not be appropriate for all use cases. Most databases appear to benefit from some curation (quality filtering), though sequence clustering appears detrimental to database quality. Finally, we demonstrate the breadth and extensibility of RESCRIPt for reproducible workflows with a comparison of global hepatitis genomes. RESCRIPt provides tools to democratize the process of reference database acquisition and management, enabling researchers to reproducibly and transparently create reference materials for diverse research applications. RESCRIPt is released under a permissive BSD-3 license at https://github.com/bokulich-lab/RESCRIPt. Public Library of Science 2021-11-08 /pmc/articles/PMC8601625/ /pubmed/34748542 http://dx.doi.org/10.1371/journal.pcbi.1009581 Text en © 2021 Robeson, II et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Robeson, Michael S. O’Rourke, Devon R. Kaehler, Benjamin D. Ziemski, Michal Dillon, Matthew R. Foster, Jeffrey T. Bokulich, Nicholas A. RESCRIPt: Reproducible sequence taxonomy reference database management |
title | RESCRIPt: Reproducible sequence taxonomy reference database management |
title_full | RESCRIPt: Reproducible sequence taxonomy reference database management |
title_fullStr | RESCRIPt: Reproducible sequence taxonomy reference database management |
title_full_unstemmed | RESCRIPt: Reproducible sequence taxonomy reference database management |
title_short | RESCRIPt: Reproducible sequence taxonomy reference database management |
title_sort | rescript: reproducible sequence taxonomy reference database management |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8601625/ https://www.ncbi.nlm.nih.gov/pubmed/34748542 http://dx.doi.org/10.1371/journal.pcbi.1009581 |
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