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MiRKAT-S: a community-level test of association between the microbiota and survival times
BACKGROUND: Community-level analysis of the human microbiota has culminated in the discovery of relationships between overall shifts in the microbiota and a wide range of diseases and conditions. However, existing work has primarily focused on analysis of relatively simple dichotomous or quantitativ...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5299808/ https://www.ncbi.nlm.nih.gov/pubmed/28179014 http://dx.doi.org/10.1186/s40168-017-0239-9 |
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author | Plantinga, Anna Zhan, Xiang Zhao, Ni Chen, Jun Jenq, Robert R. Wu, Michael C. |
author_facet | Plantinga, Anna Zhan, Xiang Zhao, Ni Chen, Jun Jenq, Robert R. Wu, Michael C. |
author_sort | Plantinga, Anna |
collection | PubMed |
description | BACKGROUND: Community-level analysis of the human microbiota has culminated in the discovery of relationships between overall shifts in the microbiota and a wide range of diseases and conditions. However, existing work has primarily focused on analysis of relatively simple dichotomous or quantitative outcomes, for example, disease status or biomarker levels. Recently, there is also considerable interest in the relationship between the microbiota and censored survival outcomes, such as in clinical trials. How to conduct community-level analysis with censored survival outcomes is unclear, since standard dissimilarity-based tests cannot accommodate censored survival times and no alternative methods exist. METHODS: We develop a new approach, MiRKAT-S, for community-level analysis of microbiome data with censored survival times. MiRKAT-S uses ecologically informative distance metrics, such as the UniFrac distances, to generate matrices of pairwise distances between individuals’ taxonomic profiles. The distance matrices are transformed into kernel (similarity) matrices, which are used to compare similarity in the microbiota to similarity in survival times between individuals. RESULTS: Simulation studies using synthetic microbial communities demonstrate correct control of type I error and adequate power. We also apply MiRKAT-S to examine the relationship between the gut microbiota and survival after allogeneic blood or bone marrow transplant. CONCLUSIONS: We present MiRKAT-S, a method that facilitates community-level analysis of the association between the microbiota and survival outcomes and therefore provides a new approach to analysis of microbiome data arising from clinical trials. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-017-0239-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-5299808 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-52998082017-02-13 MiRKAT-S: a community-level test of association between the microbiota and survival times Plantinga, Anna Zhan, Xiang Zhao, Ni Chen, Jun Jenq, Robert R. Wu, Michael C. Microbiome Methodology BACKGROUND: Community-level analysis of the human microbiota has culminated in the discovery of relationships between overall shifts in the microbiota and a wide range of diseases and conditions. However, existing work has primarily focused on analysis of relatively simple dichotomous or quantitative outcomes, for example, disease status or biomarker levels. Recently, there is also considerable interest in the relationship between the microbiota and censored survival outcomes, such as in clinical trials. How to conduct community-level analysis with censored survival outcomes is unclear, since standard dissimilarity-based tests cannot accommodate censored survival times and no alternative methods exist. METHODS: We develop a new approach, MiRKAT-S, for community-level analysis of microbiome data with censored survival times. MiRKAT-S uses ecologically informative distance metrics, such as the UniFrac distances, to generate matrices of pairwise distances between individuals’ taxonomic profiles. The distance matrices are transformed into kernel (similarity) matrices, which are used to compare similarity in the microbiota to similarity in survival times between individuals. RESULTS: Simulation studies using synthetic microbial communities demonstrate correct control of type I error and adequate power. We also apply MiRKAT-S to examine the relationship between the gut microbiota and survival after allogeneic blood or bone marrow transplant. CONCLUSIONS: We present MiRKAT-S, a method that facilitates community-level analysis of the association between the microbiota and survival outcomes and therefore provides a new approach to analysis of microbiome data arising from clinical trials. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40168-017-0239-9) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-08 /pmc/articles/PMC5299808/ /pubmed/28179014 http://dx.doi.org/10.1186/s40168-017-0239-9 Text en © The Author(s) 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License(http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver(http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Methodology Plantinga, Anna Zhan, Xiang Zhao, Ni Chen, Jun Jenq, Robert R. Wu, Michael C. MiRKAT-S: a community-level test of association between the microbiota and survival times |
title | MiRKAT-S: a community-level test of association between the microbiota and survival times |
title_full | MiRKAT-S: a community-level test of association between the microbiota and survival times |
title_fullStr | MiRKAT-S: a community-level test of association between the microbiota and survival times |
title_full_unstemmed | MiRKAT-S: a community-level test of association between the microbiota and survival times |
title_short | MiRKAT-S: a community-level test of association between the microbiota and survival times |
title_sort | mirkat-s: a community-level test of association between the microbiota and survival times |
topic | Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5299808/ https://www.ncbi.nlm.nih.gov/pubmed/28179014 http://dx.doi.org/10.1186/s40168-017-0239-9 |
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