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benchdamic: benchmarking of differential abundance methods for microbiome data

SUMMARY: Recently, an increasing number of methodological approaches have been proposed to tackle the complexity of metagenomics and microbiome data. In this scenario, reproducibility and replicability have become two critical issues, and the development of computational frameworks for the comparati...

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Autores principales: Calgaro, Matteo, Romualdi, Chiara, Risso, Davide, Vitulo, Nicola
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825737/
https://www.ncbi.nlm.nih.gov/pubmed/36477500
http://dx.doi.org/10.1093/bioinformatics/btac778
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author Calgaro, Matteo
Romualdi, Chiara
Risso, Davide
Vitulo, Nicola
author_facet Calgaro, Matteo
Romualdi, Chiara
Risso, Davide
Vitulo, Nicola
author_sort Calgaro, Matteo
collection PubMed
description SUMMARY: Recently, an increasing number of methodological approaches have been proposed to tackle the complexity of metagenomics and microbiome data. In this scenario, reproducibility and replicability have become two critical issues, and the development of computational frameworks for the comparative evaluations of such methods is of utmost importance. Here, we present benchdamic, a Bioconductor package to benchmark methods for the identification of differentially abundant taxa. AVAILABILITY AND IMPLEMENTATION: benchdamic is available as an open-source R package through the Bioconductor project at https://bioconductor.org/packages/benchdamic/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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spelling pubmed-98257372023-01-10 benchdamic: benchmarking of differential abundance methods for microbiome data Calgaro, Matteo Romualdi, Chiara Risso, Davide Vitulo, Nicola Bioinformatics Applications Note SUMMARY: Recently, an increasing number of methodological approaches have been proposed to tackle the complexity of metagenomics and microbiome data. In this scenario, reproducibility and replicability have become two critical issues, and the development of computational frameworks for the comparative evaluations of such methods is of utmost importance. Here, we present benchdamic, a Bioconductor package to benchmark methods for the identification of differentially abundant taxa. AVAILABILITY AND IMPLEMENTATION: benchdamic is available as an open-source R package through the Bioconductor project at https://bioconductor.org/packages/benchdamic/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2022-12-07 /pmc/articles/PMC9825737/ /pubmed/36477500 http://dx.doi.org/10.1093/bioinformatics/btac778 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
Calgaro, Matteo
Romualdi, Chiara
Risso, Davide
Vitulo, Nicola
benchdamic: benchmarking of differential abundance methods for microbiome data
title benchdamic: benchmarking of differential abundance methods for microbiome data
title_full benchdamic: benchmarking of differential abundance methods for microbiome data
title_fullStr benchdamic: benchmarking of differential abundance methods for microbiome data
title_full_unstemmed benchdamic: benchmarking of differential abundance methods for microbiome data
title_short benchdamic: benchmarking of differential abundance methods for microbiome data
title_sort benchdamic: benchmarking of differential abundance methods for microbiome data
topic Applications Note
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9825737/
https://www.ncbi.nlm.nih.gov/pubmed/36477500
http://dx.doi.org/10.1093/bioinformatics/btac778
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