{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,17]],"date-time":"2026-01-17T19:16:25Z","timestamp":1768677385242,"version":"3.49.0"},"reference-count":14,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T00:00:00Z","timestamp":1654473600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T00:00:00Z","timestamp":1654473600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["11971017"],"award-info":[{"award-number":["11971017"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["BMC Bioinformatics"],"published-print":{"date-parts":[[2022,12]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec>\n                <jats:title>Background<\/jats:title>\n                <jats:p>Modern sequencing technologies have generated low-cost microbiome survey datasets, across sample sites, conditions, and treatments, on an unprecedented scale and throughput. These datasets often come with a phylogenetic tree that provides a unique opportunity to examine how shared evolutionary history affects the different patterns in host-associated microbial communities.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Results<\/jats:title>\n                <jats:p>In this paper, we describe an R package, phyloMDA, for phylogeny-aware microbiome data analysis. It includes the Dirichlet-tree multinomial model for multivariate abundance data, tree-guided empirical Bayes estimation of microbial compositions, and tree-based multiscale regression methods with relative abundances as predictors.<\/jats:p>\n              <\/jats:sec><jats:sec>\n                <jats:title>Conclusion<\/jats:title>\n                <jats:p>phyloMDA is a versatile and user-friendly tool to analyze microbiome data while incorporating the phylogenetic information and addressing some of the challenges posed by the data.<\/jats:p>\n              <\/jats:sec>","DOI":"10.1186\/s12859-022-04744-5","type":"journal-article","created":{"date-parts":[[2022,6,6]],"date-time":"2022-06-06T07:03:53Z","timestamp":1654499033000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["phyloMDA: an R package for phylogeny-aware microbiome data analysis"],"prefix":"10.1186","volume":"23","author":[{"given":"Tiantian","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chao","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huimin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongyu","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1218-4017","authenticated-orcid":false,"given":"Tao","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,6,6]]},"reference":[{"issue":"1","key":"4744_CR1","doi-asserted-by":"publisher","first-page":"27","DOI":"10.1186\/s40168-017-0237-y","volume":"5","author":"S Weiss","year":"2017","unstructured":"Weiss S, Xu ZZ, Peddada S, Amir A, Bittinger K, Gonzalez A, et al. Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome. 2017;5(1):27.","journal-title":"Microbiome"},{"issue":"6","key":"4744_CR2","doi-asserted-by":"publisher","first-page":"652","DOI":"10.1038\/s41564-018-0156-0","volume":"3","author":"AD Washburne","year":"2018","unstructured":"Washburne AD, Morton JT, Sanders J, McDonald D, Zhu Q, Oliverio AM, et al. Methods for phylogenetic analysis of microbiome data. Nat Microbiol. 2018;3(6):652\u201361.","journal-title":"Nat Microbiol"},{"key":"4744_CR3","doi-asserted-by":"crossref","unstructured":"Zhu Q, Huang S, Gonzalez A, McGrath I, McDonald D, Haiminen N et al. OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures. bioRxiv 2021.","DOI":"10.1101\/2021.04.04.438427"},{"key":"4744_CR4","volume-title":"Statistical analysis of microbiome data","author":"T Wang","year":"2021","unstructured":"Wang T, Zhao H. 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