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Rigorous Statistical Methods for Rigorous Microbiome Science
High-throughput sequencing has facilitated discovery in microbiome science, but distinguishing true discoveries from spurious signals can be challenging. The Statistical Diversity Lab develops rigorous statistical methods and statistical software for the analysis of microbiome and biodiversity data....
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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American Society for Microbiology
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584874/ https://www.ncbi.nlm.nih.gov/pubmed/31138722 http://dx.doi.org/10.1128/mSystems.00117-19 |
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author | Willis, Amy D. |
author_facet | Willis, Amy D. |
author_sort | Willis, Amy D. |
collection | PubMed |
description | High-throughput sequencing has facilitated discovery in microbiome science, but distinguishing true discoveries from spurious signals can be challenging. The Statistical Diversity Lab develops rigorous statistical methods and statistical software for the analysis of microbiome and biodiversity data. Developing statistical methods that produce valid P values requires thoughtful modeling and careful validation, but careful statistical analysis reduces the risk of false discoveries and increases scientific understanding. |
format | Online Article Text |
id | pubmed-6584874 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | American Society for Microbiology |
record_format | MEDLINE/PubMed |
spelling | pubmed-65848742019-07-03 Rigorous Statistical Methods for Rigorous Microbiome Science Willis, Amy D. mSystems Perspective High-throughput sequencing has facilitated discovery in microbiome science, but distinguishing true discoveries from spurious signals can be challenging. The Statistical Diversity Lab develops rigorous statistical methods and statistical software for the analysis of microbiome and biodiversity data. Developing statistical methods that produce valid P values requires thoughtful modeling and careful validation, but careful statistical analysis reduces the risk of false discoveries and increases scientific understanding. American Society for Microbiology 2019-05-28 /pmc/articles/PMC6584874/ /pubmed/31138722 http://dx.doi.org/10.1128/mSystems.00117-19 Text en Copyright © 2019 Willis. https://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Perspective Willis, Amy D. Rigorous Statistical Methods for Rigorous Microbiome Science |
title | Rigorous Statistical Methods for Rigorous Microbiome Science |
title_full | Rigorous Statistical Methods for Rigorous Microbiome Science |
title_fullStr | Rigorous Statistical Methods for Rigorous Microbiome Science |
title_full_unstemmed | Rigorous Statistical Methods for Rigorous Microbiome Science |
title_short | Rigorous Statistical Methods for Rigorous Microbiome Science |
title_sort | rigorous statistical methods for rigorous microbiome science |
topic | Perspective |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584874/ https://www.ncbi.nlm.nih.gov/pubmed/31138722 http://dx.doi.org/10.1128/mSystems.00117-19 |
work_keys_str_mv | AT willisamyd rigorousstatisticalmethodsforrigorousmicrobiomescience |