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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...

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Detalles Bibliográficos
Autores principales: Douglas, Gavin M, Kim, Sunu, Langille, Morgan G I, Shapiro, B Jesse
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
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.
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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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