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GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes
Large-scale metagenomic datasets enable the recovery of hundreds of population genomes from environmental samples. However, these genomes do not typically represent the full diversity of complex microbial communities. Gene-centric approaches can be used to gain a comprehensive view of diversity by e...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6007438/ https://www.ncbi.nlm.nih.gov/pubmed/29562347 http://dx.doi.org/10.1093/nar/gky174 |
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author | Boyd, Joel A Woodcroft, Ben J Tyson, Gene W |
author_facet | Boyd, Joel A Woodcroft, Ben J Tyson, Gene W |
author_sort | Boyd, Joel A |
collection | PubMed |
description | Large-scale metagenomic datasets enable the recovery of hundreds of population genomes from environmental samples. However, these genomes do not typically represent the full diversity of complex microbial communities. Gene-centric approaches can be used to gain a comprehensive view of diversity by examining each read independently, but traditional pairwise comparison approaches typically over-classify taxonomy and scale poorly with increasing metagenome and database sizes. Here we introduce GraftM, a tool that uses gene specific packages to rapidly identify gene families in metagenomic data using hidden Markov models (HMMs) or DIAMOND databases, and classifies these sequences using placement into pre-constructed gene trees. The speed and accuracy of GraftM was benchmarked with in silico and in vitro mock communities using taxonomic markers, and was found to have higher accuracy at the family level with a processing time 2.0–3.7× faster than currently available software. Exploration of a wetland metagenome using 16S rRNA- and methyl-coenzyme M reductase (McrA)-specific gpkgs revealed taxonomic and functional shifts across a depth gradient. Analysis of the NCBI nr database using the McrA gpkg allowed the detection of novel sequences belonging to phylum-level lineages. A growing collection of gpkgs is available online (https://github.com/geronimp/graftM_gpkgs), where curated packages can be uploaded and exchanged. |
format | Online Article Text |
id | pubmed-6007438 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-60074382018-07-05 GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes Boyd, Joel A Woodcroft, Ben J Tyson, Gene W Nucleic Acids Res Methods Online Large-scale metagenomic datasets enable the recovery of hundreds of population genomes from environmental samples. However, these genomes do not typically represent the full diversity of complex microbial communities. Gene-centric approaches can be used to gain a comprehensive view of diversity by examining each read independently, but traditional pairwise comparison approaches typically over-classify taxonomy and scale poorly with increasing metagenome and database sizes. Here we introduce GraftM, a tool that uses gene specific packages to rapidly identify gene families in metagenomic data using hidden Markov models (HMMs) or DIAMOND databases, and classifies these sequences using placement into pre-constructed gene trees. The speed and accuracy of GraftM was benchmarked with in silico and in vitro mock communities using taxonomic markers, and was found to have higher accuracy at the family level with a processing time 2.0–3.7× faster than currently available software. Exploration of a wetland metagenome using 16S rRNA- and methyl-coenzyme M reductase (McrA)-specific gpkgs revealed taxonomic and functional shifts across a depth gradient. Analysis of the NCBI nr database using the McrA gpkg allowed the detection of novel sequences belonging to phylum-level lineages. A growing collection of gpkgs is available online (https://github.com/geronimp/graftM_gpkgs), where curated packages can be uploaded and exchanged. Oxford University Press 2018-06-01 2018-03-19 /pmc/articles/PMC6007438/ /pubmed/29562347 http://dx.doi.org/10.1093/nar/gky174 Text en © The Author(s) 2018. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Methods Online Boyd, Joel A Woodcroft, Ben J Tyson, Gene W GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes |
title | GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes |
title_full | GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes |
title_fullStr | GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes |
title_full_unstemmed | GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes |
title_short | GraftM: a tool for scalable, phylogenetically informed classification of genes within metagenomes |
title_sort | graftm: a tool for scalable, phylogenetically informed classification of genes within metagenomes |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6007438/ https://www.ncbi.nlm.nih.gov/pubmed/29562347 http://dx.doi.org/10.1093/nar/gky174 |
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