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MetaSanity: an integrated microbial genome evaluation and annotation pipeline

SUMMARY: As the importance of microbiome research continues to become more prevalent and essential to understanding a wide variety of ecosystems (e.g. marine, built, host associated, etc.), there is a need for researchers to be able to perform highly reproducible and quality analysis of microbial ge...

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Detalles Bibliográficos
Autores principales: Neely, Christopher J, Graham, Elaina D, Tully, Benjamin J
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520038/
https://www.ncbi.nlm.nih.gov/pubmed/32426808
http://dx.doi.org/10.1093/bioinformatics/btaa512
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author Neely, Christopher J
Graham, Elaina D
Tully, Benjamin J
author_facet Neely, Christopher J
Graham, Elaina D
Tully, Benjamin J
author_sort Neely, Christopher J
collection PubMed
description SUMMARY: As the importance of microbiome research continues to become more prevalent and essential to understanding a wide variety of ecosystems (e.g. marine, built, host associated, etc.), there is a need for researchers to be able to perform highly reproducible and quality analysis of microbial genomes. MetaSanity incorporates analyses from 11 existing and widely used genome evaluation and annotation suites into a single, distributable workflow, thereby decreasing the workload of microbiologists by allowing for a flexible, expansive data analysis pipeline. MetaSanity has been designed to provide separate, reproducible workflows that (i) can determine the overall quality of a microbial genome, while providing a putative phylogenetic assignment, and (ii) can assign structural and functional gene annotations with varying degrees of specificity to suit the needs of the researcher. The software suite combines the results from several tools to provide broad insights into overall metabolic function. Importantly, this software provides built-in optimization for ‘big data’ analysis by storing all relevant outputs in an SQL database, allowing users to query all the results for the elements that will most impact their research. AVAILABILITY AND IMPLEMENTATION: MetaSanity is provided under the GNU General Public License v.3.0 and is available for download at https://github.com/cjneely10/MetaSanity. This application is distributed as a Docker image. MetaSanity is implemented in Python3/Cython and C++. Instructions for its installation and use are available within the GitHub wiki page at https://github.com/cjneely10/MetaSanity/wiki, and additional instructions are available at https://cjneely10.github.io/year-archive/. MetaSanity is optimized for users with limited programing experience. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-75200382020-09-30 MetaSanity: an integrated microbial genome evaluation and annotation pipeline Neely, Christopher J Graham, Elaina D Tully, Benjamin J Bioinformatics Applications Notes SUMMARY: As the importance of microbiome research continues to become more prevalent and essential to understanding a wide variety of ecosystems (e.g. marine, built, host associated, etc.), there is a need for researchers to be able to perform highly reproducible and quality analysis of microbial genomes. MetaSanity incorporates analyses from 11 existing and widely used genome evaluation and annotation suites into a single, distributable workflow, thereby decreasing the workload of microbiologists by allowing for a flexible, expansive data analysis pipeline. MetaSanity has been designed to provide separate, reproducible workflows that (i) can determine the overall quality of a microbial genome, while providing a putative phylogenetic assignment, and (ii) can assign structural and functional gene annotations with varying degrees of specificity to suit the needs of the researcher. The software suite combines the results from several tools to provide broad insights into overall metabolic function. Importantly, this software provides built-in optimization for ‘big data’ analysis by storing all relevant outputs in an SQL database, allowing users to query all the results for the elements that will most impact their research. AVAILABILITY AND IMPLEMENTATION: MetaSanity is provided under the GNU General Public License v.3.0 and is available for download at https://github.com/cjneely10/MetaSanity. This application is distributed as a Docker image. MetaSanity is implemented in Python3/Cython and C++. Instructions for its installation and use are available within the GitHub wiki page at https://github.com/cjneely10/MetaSanity/wiki, and additional instructions are available at https://cjneely10.github.io/year-archive/. MetaSanity is optimized for users with limited programing experience. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2020-05-19 /pmc/articles/PMC7520038/ /pubmed/32426808 http://dx.doi.org/10.1093/bioinformatics/btaa512 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Applications Notes
Neely, Christopher J
Graham, Elaina D
Tully, Benjamin J
MetaSanity: an integrated microbial genome evaluation and annotation pipeline
title MetaSanity: an integrated microbial genome evaluation and annotation pipeline
title_full MetaSanity: an integrated microbial genome evaluation and annotation pipeline
title_fullStr MetaSanity: an integrated microbial genome evaluation and annotation pipeline
title_full_unstemmed MetaSanity: an integrated microbial genome evaluation and annotation pipeline
title_short MetaSanity: an integrated microbial genome evaluation and annotation pipeline
title_sort metasanity: an integrated microbial genome evaluation and annotation pipeline
topic Applications Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7520038/
https://www.ncbi.nlm.nih.gov/pubmed/32426808
http://dx.doi.org/10.1093/bioinformatics/btaa512
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