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Efficient computation of contributional diversity metrics from microbiome data with FuncDiv
MOTIVATION: Microbiome datasets with taxa linked to the functions (e.g. genes) they encode are becoming more common as metagenomics sequencing approaches improve. However, these data are challenging to analyze due to their complexity. Summary metrics, such as the alpha and beta diversity of taxa con...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825779/ https://www.ncbi.nlm.nih.gov/pubmed/36519836 http://dx.doi.org/10.1093/bioinformatics/btac809 |
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author | Douglas, Gavin M Kim, Sunu Langille, Morgan G I Shapiro, B Jesse |
author_facet | Douglas, Gavin M Kim, Sunu Langille, Morgan G I Shapiro, B Jesse |
author_sort | Douglas, Gavin M |
collection | PubMed |
description | MOTIVATION: Microbiome datasets with taxa linked to the functions (e.g. genes) they encode are becoming more common as metagenomics sequencing approaches improve. However, these data are challenging to analyze due to their complexity. Summary metrics, such as the alpha and beta diversity of taxa contributing to each function (i.e. contributional diversity), represent one approach to investigate these data, but currently there are no straightforward methods for doing so. RESULTS: We addressed this gap by developing FuncDiv, which efficiently performs these computations. Contributional diversity metrics can provide novel insights that would be impossible to identify without jointly considering taxa and functions. AVAILABILITY AND IMPLEMENTATION: FuncDiv is distributed under a GNU Affero General Public License v3.0 and is available at https://github.com/gavinmdouglas/FuncDiv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-9825779 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-98257792023-01-10 Efficient computation of contributional diversity metrics from microbiome data with FuncDiv Douglas, Gavin M Kim, Sunu Langille, Morgan G I Shapiro, B Jesse Bioinformatics Applications Note MOTIVATION: Microbiome datasets with taxa linked to the functions (e.g. genes) they encode are becoming more common as metagenomics sequencing approaches improve. However, these data are challenging to analyze due to their complexity. Summary metrics, such as the alpha and beta diversity of taxa contributing to each function (i.e. contributional diversity), represent one approach to investigate these data, but currently there are no straightforward methods for doing so. RESULTS: We addressed this gap by developing FuncDiv, which efficiently performs these computations. Contributional diversity metrics can provide novel insights that would be impossible to identify without jointly considering taxa and functions. AVAILABILITY AND IMPLEMENTATION: FuncDiv is distributed under a GNU Affero General Public License v3.0 and is available at https://github.com/gavinmdouglas/FuncDiv. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-12-15 /pmc/articles/PMC9825779/ /pubmed/36519836 http://dx.doi.org/10.1093/bioinformatics/btac809 Text en © The Author(s) 2022. Published by Oxford University Press. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Applications Note Douglas, Gavin M Kim, Sunu Langille, Morgan G I Shapiro, B Jesse Efficient computation of contributional diversity metrics from microbiome data with FuncDiv |
title | Efficient computation of contributional diversity metrics from microbiome data with FuncDiv |
title_full | Efficient computation of contributional diversity metrics from microbiome data with FuncDiv |
title_fullStr | Efficient computation of contributional diversity metrics from microbiome data with FuncDiv |
title_full_unstemmed | Efficient computation of contributional diversity metrics from microbiome data with FuncDiv |
title_short | Efficient computation of contributional diversity metrics from microbiome data with FuncDiv |
title_sort | efficient computation of contributional diversity metrics from microbiome data with funcdiv |
topic | Applications Note |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825779/ https://www.ncbi.nlm.nih.gov/pubmed/36519836 http://dx.doi.org/10.1093/bioinformatics/btac809 |
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