{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T03:49:08Z","timestamp":1772768948153,"version":"3.50.1"},"reference-count":34,"publisher":"Oxford University Press (OUP)","issue":"9","license":[{"start":{"date-parts":[[2016,12,21]],"date-time":"2016-12-21T00:00:00Z","timestamp":1482278400000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["5K12HD043483-14"],"award-info":[{"award-number":["5K12HD043483-14"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,5,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:sec><jats:title>Motivation<\/jats:title><jats:p>Association analysis of microbiome composition with disease-related outcomes provides invaluable knowledge towards understanding the roles of microbes in the underlying disease mechanisms. Proper analysis of sparse compositional microbiome data is challenging. Existing methods rely on strong assumptions on the data structure and fail to pinpoint the associated microbial communities.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results<\/jats:title><jats:p>We develop a general framework to: (i) perform robust association tests for the microbial community that exhibits arbitrary inter-taxa dependencies; (ii) localize lineages on the taxonomic tree that are associated with covariates (e.g. disease status); and (iii) assess the overall association of the whole microbial community with the covariates. Unlike existing methods for microbiome association analysis, our framework does not make any distributional assumptions on the microbiome data; it allows for the adjustment of confounding variables and accommodates excessive zero observations; and it incorporates taxonomic information. We perform extensive simulation studies under a wide-range of scenarios to evaluate the new methods and demonstrate substantial power gain over existing methods. The advantages of the proposed framework are further demonstrated with real datasets from two microbiome studies. The relevant R package miLineage is publicly available.<\/jats:p><\/jats:sec><jats:sec><jats:title>Availability and Implementation<\/jats:title><jats:p>miLineage package, manual and tutorial are available at https:\/\/medschool.vanderbilt.edu\/tang-lab\/software\/miLineage.<\/jats:p><\/jats:sec><jats:sec><jats:title>Supplementary information<\/jats:title><jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p><\/jats:sec>","DOI":"10.1093\/bioinformatics\/btw804","type":"journal-article","created":{"date-parts":[[2016,12,14]],"date-time":"2016-12-14T20:07:02Z","timestamp":1481746022000},"page":"1278-1285","source":"Crossref","is-referenced-by-count":43,"title":["A general framework for association analysis of microbial communities on a taxonomic tree"],"prefix":"10.1093","volume":"33","author":[{"given":"Zheng-Zheng","family":"Tang","sequence":"first","affiliation":[{"name":"Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, USA"}]},{"given":"Guanhua","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Vanderbilt University School of Medicine, Nashville, TN, USA"}]},{"given":"Alexander V","family":"Alekseyenko","sequence":"additional","affiliation":[{"name":"Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA"},{"name":"Department of Oral Health Sciences, Medical University of South Carolina, Charleston, SC, USA"}]},{"given":"Hongzhe","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Epidemiology, University of Pennsylvania School of Medicine, Philadelphia, PA, USA"}]}],"member":"286","published-online":{"date-parts":[[2016,12,21]]},"reference":[{"key":"2023020205024842000_btw804-B1","doi-asserted-by":"crossref","first-page":"31.","DOI":"10.1186\/2049-2618-1-31","article-title":"Community differentiation of the cutaneous microbiota in psoriasis","volume":"1","author":"Alekseyenko","year":"2013","journal-title":"Microbiome"},{"key":"2023020205024842000_btw804-B2","first-page":"32","article-title":"A new method for non-parametric multivariate analysis of variance","volume":"26","author":"Anderson","year":"2001","journal-title":"Austral. 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