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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...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Chongqing Medical University
2017
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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. |
format | Online Article Text |
id | pubmed-6128532 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Chongqing Medical University |
record_format | MEDLINE/PubMed |
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 |
work_keys_str_mv | AT xiayinglin hypothesistestingandstatisticalanalysisofmicrobiome AT sunjun hypothesistestingandstatisticalanalysisofmicrobiome |