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Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale
The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580927/ https://www.ncbi.nlm.nih.gov/pubmed/36303775 http://dx.doi.org/10.3389/fbinf.2021.826370 |
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author | Hu, Bin Canon, Shane Eloe-Fadrosh, Emiley A. Anubhav, Babinski, Michal Corilo, Yuri Davenport, Karen Duncan, William D. Fagnan, Kjiersten Flynn, Mark Foster, Brian Hays, David Huntemann, Marcel Jackson, Elais K. Player Kelliher, Julia Li, Po-E. Lo, Chien-Chi Mans, Douglas McCue, Lee Ann Mouncey, Nigel Mungall, Christopher J. Piehowski, Paul D. Purvine, Samuel O. Smith, Montana Varghese, Neha Jacob Winston, Donald Xu, Yan Chain, Patrick S. G. |
author_facet | Hu, Bin Canon, Shane Eloe-Fadrosh, Emiley A. Anubhav, Babinski, Michal Corilo, Yuri Davenport, Karen Duncan, William D. Fagnan, Kjiersten Flynn, Mark Foster, Brian Hays, David Huntemann, Marcel Jackson, Elais K. Player Kelliher, Julia Li, Po-E. Lo, Chien-Chi Mans, Douglas McCue, Lee Ann Mouncey, Nigel Mungall, Christopher J. Piehowski, Paul D. Purvine, Samuel O. Smith, Montana Varghese, Neha Jacob Winston, Donald Xu, Yan Chain, Patrick S. G. |
author_sort | Hu, Bin |
collection | PubMed |
description | The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges. |
format | Online Article Text |
id | pubmed-9580927 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-95809272022-10-26 Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale Hu, Bin Canon, Shane Eloe-Fadrosh, Emiley A. Anubhav, Babinski, Michal Corilo, Yuri Davenport, Karen Duncan, William D. Fagnan, Kjiersten Flynn, Mark Foster, Brian Hays, David Huntemann, Marcel Jackson, Elais K. Player Kelliher, Julia Li, Po-E. Lo, Chien-Chi Mans, Douglas McCue, Lee Ann Mouncey, Nigel Mungall, Christopher J. Piehowski, Paul D. Purvine, Samuel O. Smith, Montana Varghese, Neha Jacob Winston, Donald Xu, Yan Chain, Patrick S. G. Front Bioinform Bioinformatics The nascent field of microbiome science is transitioning from a descriptive approach of cataloging taxa and functions present in an environment to applying multi-omics methods to investigate microbiome dynamics and function. A large number of new tools and algorithms have been designed and used for very specific purposes on samples collected by individual investigators or groups. While these developments have been quite instructive, the ability to compare microbiome data generated by many groups of researchers is impeded by the lack of standardized application of bioinformatics methods. Additionally, there are few examples of broad bioinformatics workflows that can process metagenome, metatranscriptome, metaproteome and metabolomic data at scale, and no central hub that allows processing, or provides varied omics data that are findable, accessible, interoperable and reusable (FAIR). Here, we review some of the challenges that exist in analyzing omics data within the microbiome research sphere, and provide context on how the National Microbiome Data Collaborative has adopted a standardized and open access approach to address such challenges. Frontiers Media S.A. 2022-01-17 /pmc/articles/PMC9580927/ /pubmed/36303775 http://dx.doi.org/10.3389/fbinf.2021.826370 Text en Copyright © 2022 Hu, Canon, Eloe-Fadrosh, Anubhav, Babinski, Corilo, Davenport, Duncan, Fagnan, Flynn, Foster, Hays, Huntemann, Jackson, Kelliher, Li, Lo, Mans, McCue, Mouncey, Mungall, Piehowski, Purvine, Smith, Varghese, Winston, Xu and Chain. https://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) and the copyright owner(s) 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 | Bioinformatics Hu, Bin Canon, Shane Eloe-Fadrosh, Emiley A. Anubhav, Babinski, Michal Corilo, Yuri Davenport, Karen Duncan, William D. Fagnan, Kjiersten Flynn, Mark Foster, Brian Hays, David Huntemann, Marcel Jackson, Elais K. Player Kelliher, Julia Li, Po-E. Lo, Chien-Chi Mans, Douglas McCue, Lee Ann Mouncey, Nigel Mungall, Christopher J. Piehowski, Paul D. Purvine, Samuel O. Smith, Montana Varghese, Neha Jacob Winston, Donald Xu, Yan Chain, Patrick S. G. Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale |
title | Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale |
title_full | Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale |
title_fullStr | Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale |
title_full_unstemmed | Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale |
title_short | Challenges in Bioinformatics Workflows for Processing Microbiome Omics Data at Scale |
title_sort | challenges in bioinformatics workflows for processing microbiome omics data at scale |
topic | Bioinformatics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9580927/ https://www.ncbi.nlm.nih.gov/pubmed/36303775 http://dx.doi.org/10.3389/fbinf.2021.826370 |
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