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Flex Meta-Storms elucidates the microbiome local beta-diversity under specific phenotypes
MOTIVATION: Beta-diversity quantitatively measures the difference among microbial communities thus enlightening the association between microbiome composition and environment properties or host phenotypes. The beta-diversity analysis mainly relies on distances among microbiomes that are calculated b...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082668/ https://www.ncbi.nlm.nih.gov/pubmed/36946295 http://dx.doi.org/10.1093/bioinformatics/btad148 |
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author | Zhang, Mingqian Zhang, Wenke Chen, Yuzhu Zhao, Jin Wu, Shunyao Su, Xiaoquan |
author_facet | Zhang, Mingqian Zhang, Wenke Chen, Yuzhu Zhao, Jin Wu, Shunyao Su, Xiaoquan |
author_sort | Zhang, Mingqian |
collection | PubMed |
description | MOTIVATION: Beta-diversity quantitatively measures the difference among microbial communities thus enlightening the association between microbiome composition and environment properties or host phenotypes. The beta-diversity analysis mainly relies on distances among microbiomes that are calculated by all microbial features. However, in some cases, only a small fraction of members in a community plays crucial roles. Such a tiny proportion is insufficient to alter the overall distance, which is always missed by end-to-end comparison. On the other hand, beta-diversity pattern can also be interfered due to the data sparsity when only focusing on nonabundant microbes. RESULTS: Here, we develop Flex Meta-Storms (FMS) distance algorithm that implements the “local alignment” of microbiomes for the first time. Using a flexible extraction that considers the weighted phylogenetic and functional relations of microbes, FMS produces a normalized phylogenetic distance among members of interest for microbiome pairs. We demonstrated the advantage of FMS in detecting the subtle variations of microbiomes among different states using artificial and real datasets, which were neglected by regular distance metrics. Therefore, FMS effectively discriminates microbiomes with higher sensitivity and flexibility, thus contributing to in-depth comprehension of microbe–host interactions, as well as promoting the utilization of microbiome data such as disease screening and prediction. AVAILABILITY AND IMPLEMENTATION: FMS is implemented in C++, and the source code is released at https://github.com/qdu-bioinfo/flex-meta-storms. |
format | Online Article Text |
id | pubmed-10082668 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-100826682023-04-09 Flex Meta-Storms elucidates the microbiome local beta-diversity under specific phenotypes Zhang, Mingqian Zhang, Wenke Chen, Yuzhu Zhao, Jin Wu, Shunyao Su, Xiaoquan Bioinformatics Original Paper MOTIVATION: Beta-diversity quantitatively measures the difference among microbial communities thus enlightening the association between microbiome composition and environment properties or host phenotypes. The beta-diversity analysis mainly relies on distances among microbiomes that are calculated by all microbial features. However, in some cases, only a small fraction of members in a community plays crucial roles. Such a tiny proportion is insufficient to alter the overall distance, which is always missed by end-to-end comparison. On the other hand, beta-diversity pattern can also be interfered due to the data sparsity when only focusing on nonabundant microbes. RESULTS: Here, we develop Flex Meta-Storms (FMS) distance algorithm that implements the “local alignment” of microbiomes for the first time. Using a flexible extraction that considers the weighted phylogenetic and functional relations of microbes, FMS produces a normalized phylogenetic distance among members of interest for microbiome pairs. We demonstrated the advantage of FMS in detecting the subtle variations of microbiomes among different states using artificial and real datasets, which were neglected by regular distance metrics. Therefore, FMS effectively discriminates microbiomes with higher sensitivity and flexibility, thus contributing to in-depth comprehension of microbe–host interactions, as well as promoting the utilization of microbiome data such as disease screening and prediction. AVAILABILITY AND IMPLEMENTATION: FMS is implemented in C++, and the source code is released at https://github.com/qdu-bioinfo/flex-meta-storms. Oxford University Press 2023-03-22 /pmc/articles/PMC10082668/ /pubmed/36946295 http://dx.doi.org/10.1093/bioinformatics/btad148 Text en © The Author(s) 2023. 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 | Original Paper Zhang, Mingqian Zhang, Wenke Chen, Yuzhu Zhao, Jin Wu, Shunyao Su, Xiaoquan Flex Meta-Storms elucidates the microbiome local beta-diversity under specific phenotypes |
title | Flex Meta-Storms elucidates the microbiome local beta-diversity under specific phenotypes |
title_full | Flex Meta-Storms elucidates the microbiome local beta-diversity under specific phenotypes |
title_fullStr | Flex Meta-Storms elucidates the microbiome local beta-diversity under specific phenotypes |
title_full_unstemmed | Flex Meta-Storms elucidates the microbiome local beta-diversity under specific phenotypes |
title_short | Flex Meta-Storms elucidates the microbiome local beta-diversity under specific phenotypes |
title_sort | flex meta-storms elucidates the microbiome local beta-diversity under specific phenotypes |
topic | Original Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10082668/ https://www.ncbi.nlm.nih.gov/pubmed/36946295 http://dx.doi.org/10.1093/bioinformatics/btad148 |
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