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Hypothesis testing and statistical analysis of microbiome

After the initiation of Human Microbiome Project in 2008, various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies. In this review and perspective, we discuss the research and statistical hypotheses in gut microbio...

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Autores principales: Xia, Yinglin, Sun, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Chongqing Medical University 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6128532/
https://www.ncbi.nlm.nih.gov/pubmed/30197908
http://dx.doi.org/10.1016/j.gendis.2017.06.001
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author Xia, Yinglin
Sun, Jun
author_facet Xia, Yinglin
Sun, Jun
author_sort Xia, Yinglin
collection PubMed
description After the initiation of Human Microbiome Project in 2008, various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies. In this review and perspective, we discuss the research and statistical hypotheses in gut microbiome studies, focusing on mechanistic concepts that underlie the complex relationships among host, microbiome, and environment. We review the current available statistic tools and highlight recent progress of newly developed statistical methods and models. Given the current challenges and limitations in biostatistic approaches and tools, we discuss the future direction in developing statistical methods and models for the microbiome studies.
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spelling pubmed-61285322018-09-07 Hypothesis testing and statistical analysis of microbiome Xia, Yinglin Sun, Jun Genes Dis Article After the initiation of Human Microbiome Project in 2008, various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies. In this review and perspective, we discuss the research and statistical hypotheses in gut microbiome studies, focusing on mechanistic concepts that underlie the complex relationships among host, microbiome, and environment. We review the current available statistic tools and highlight recent progress of newly developed statistical methods and models. Given the current challenges and limitations in biostatistic approaches and tools, we discuss the future direction in developing statistical methods and models for the microbiome studies. Chongqing Medical University 2017-06-23 /pmc/articles/PMC6128532/ /pubmed/30197908 http://dx.doi.org/10.1016/j.gendis.2017.06.001 Text en © 2017 Chongqing Medical University. Production and hosting by Elsevier B.V. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Xia, Yinglin
Sun, Jun
Hypothesis testing and statistical analysis of microbiome
title Hypothesis testing and statistical analysis of microbiome
title_full Hypothesis testing and statistical analysis of microbiome
title_fullStr Hypothesis testing and statistical analysis of microbiome
title_full_unstemmed Hypothesis testing and statistical analysis of microbiome
title_short Hypothesis testing and statistical analysis of microbiome
title_sort hypothesis testing and statistical analysis of microbiome
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6128532/
https://www.ncbi.nlm.nih.gov/pubmed/30197908
http://dx.doi.org/10.1016/j.gendis.2017.06.001
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