{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T02:46:42Z","timestamp":1772765202087,"version":"3.50.1"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"17","funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,9,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Motivation: The human microbial communities are associated with many human diseases such as obesity, diabetes and inflammatory bowel disease. High-throughput sequencing technology has been widely used to quantify the microbial composition in order to understand its impacts on human health. Longitudinal measurements of microbial communities are commonly obtained in many microbiome studies. A key question in such microbiome studies is to identify the microbes that are associated with clinical outcomes or environmental factors. However, microbiome compositional data are highly skewed, bounded in [0,1), and often sparse with many zeros. In addition, the observations from repeated measures in longitudinal studies are correlated. A method that takes into account these features is needed for association analysis in longitudinal microbiome data.<\/jats:p><jats:p>Results: In this paper, we propose a two-part zero-inflated Beta regression model with random effects (ZIBR) for testing the association between microbial abundance and clinical covariates for longitudinal microbiome data. The model includes a logistic regression component to model presence\/absence of a microbe in the samples and a Beta regression component to model non-zero microbial abundance, where each component includes a random effect to account for the correlations among the repeated measurements on the same subject. Both simulation studies and the application to real microbiome data have shown that ZIBR model outperformed the previously used methods. The method provides a useful tool for identifying the relevant taxa based on longitudinal or repeated measures in microbiome research.<\/jats:p><jats:p>Availability and Implementation: \u00a0https:\/\/github.com\/chvlyl\/ZIBR<\/jats:p><jats:p>Contact: \u00a0hongzhe@upenn.edu<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw308","type":"journal-article","created":{"date-parts":[[2016,8,7]],"date-time":"2016-08-07T00:18:02Z","timestamp":1470529082000},"page":"2611-2617","source":"Crossref","is-referenced-by-count":197,"title":["A two-part mixed-effects model for analyzing longitudinal microbiome compositional data"],"prefix":"10.1093","volume":"32","author":[{"given":"Eric Z.","family":"Chen","sequence":"first","affiliation":[{"name":"1 Genomics and Computational Biology Graduate Group"},{"name":"2 Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA"}]},{"given":"Hongzhe","family":"Li","sequence":"additional","affiliation":[{"name":"1 Genomics and Computational Biology Graduate Group"},{"name":"2 Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA 19104, USA"}]}],"member":"286","published-online":{"date-parts":[[2016,5,14]]},"reference":[{"key":"2023020112593619700_btw308-B1","doi-asserted-by":"crossref","first-page":"R106.","DOI":"10.1186\/gb-2010-11-10-r106","article-title":"Differential expression analysis for sequence count data","volume":"11","author":"Anders","year":"2010","journal-title":"Genome Biol"},{"key":"2023020112593619700_btw308-B2","doi-asserted-by":"crossref","first-page":"307ra152","DOI":"10.1126\/scitranslmed.aab2271","article-title":"Early infancy microbial and metabolic alterations affect risk of childhood asthma","volume":"7","author":"Arrieta","year":"2015","journal-title":"Sci. Transl. Med"},{"key":"2023020112593619700_btw308-B3","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1016\/j.chom.2015.04.004","article-title":"Dynamics and stabilization of the human gut microbiome during the first year of life","volume":"17","author":"B\u00e4ckhed","year":"2015","journal-title":"Cell Host Microbe"},{"key":"2023020112593619700_btw308-B4","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1111\/j.2517-6161.1995.tb02031.x","article-title":"Controlling the false discovery rate: a practical and powerful approach to multiple testing","volume":"57","author":"Benjamini","year":"1995","journal-title":"J. R. Stat. Soc. Ser. B"},{"key":"2023020112593619700_btw308-B5","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1016\/j.cell.2014.05.052","article-title":"Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences","volume":"158","author":"Cox","year":"2014","journal-title":"Cell"},{"key":"2023020112593619700_btw308-B6","doi-asserted-by":"crossref","first-page":"559+","DOI":"10.1038\/nature12820","article-title":"Diet rapidly and reproducibly alters the human gut microbiome","volume":"505","author":"David","year":"2014","journal-title":"Nature"},{"key":"2023020112593619700_btw308-B7","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1016\/j.mib.2015.04.004","article-title":"Metagenomics meets time series analysis: unraveling microbial community dynamics","volume":"25","author":"Faust","year":"2015","journal-title":"Curr. Opin. Microbiol"},{"key":"2023020112593619700_btw308-B8","doi-asserted-by":"crossref","first-page":"4131","DOI":"10.1016\/j.febslet.2014.02.037","article-title":"The dynamic microbiome","volume":"588","author":"Gerber","year":"2014","journal-title":"FEBS Lett"},{"key":"2023020112593619700_btw308-B9","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1016\/j.copbio.2011.11.017","article-title":"Characterizing microbial communities through space and time","volume":"23","author":"Gonz\u00e1lez","year":"2012","journal-title":"Curr. Opin. Biotechnol"},{"key":"2023020112593619700_btw308-B10","doi-asserted-by":"crossref","first-page":"1030","DOI":"10.1111\/j.0006-341X.2000.01030.x","article-title":"Zero-inflated Poisson and binomial regression with random effects: a case study","volume":"56","author":"Hall","year":"2000","journal-title":"Biometrics"},{"key":"2023020112593619700_btw308-B11","doi-asserted-by":"crossref","first-page":"470","DOI":"10.1016\/j.cell.2012.07.008","article-title":"Host remodeling of the gut microbiome and metabolic changes during pregnancy","volume":"150","author":"Koren","year":"2012","journal-title":"Cell"},{"key":"2023020112593619700_btw308-B12","doi-asserted-by":"crossref","first-page":"1489","DOI":"10.1053\/j.gastro.2014.02.009","article-title":"The microbiome in inflammatory bowel disease: current status and the future ahead","volume":"146","author":"Kostic","year":"2014","journal-title":"Gastroenterology"},{"key":"2023020112593619700_btw308-B13","doi-asserted-by":"crossref","first-page":"260","DOI":"10.1016\/j.chom.2015.01.001","article-title":"The dynamics of the human infant gut microbiome in development and in progression toward type 1 diabetes","volume":"17","author":"Kostic","year":"2015","journal-title":"Cell Host Microbe"},{"key":"2023020112593619700_btw308-B14","doi-asserted-by":"crossref","first-page":"12522","DOI":"10.1073\/pnas.1409497111","article-title":"Patterned progression of bacterial populations in the premature infant gut","volume":"111","author":"La Rosa","year":"2014","journal-title":"Proc. Natl. Acad. Sci. U. S. A"},{"key":"2023020112593619700_btw308-B15","doi-asserted-by":"crossref","DOI":"10.1097\/MIB.0000000000000426","article-title":"Comparative effectiveness of nutritional and biological therapy in North American children with active Crohn\u2019s disease","author":"Lee","year":"2015","journal-title":"Inflamm. Bowel Dis"},{"key":"2023020112593619700_btw308-B16","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1016\/j.chom.2015.09.008","article-title":"Inflammation, antibiotics, and diet as environmental stressors of the gut microbiome in pediatric Crohn\u2019s disease","volume":"18","author":"Lewis","year":"2015","journal-title":"Cell Host Microbe"},{"key":"2023020112593619700_btw308-B17","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1146\/annurev-statistics-010814-020351","article-title":"Microbiome, metagenomics, and high-dimensional compositional data analysis","volume":"2","author":"Li","year":"2015","journal-title":"Annu. Rev. Stat. Appl"},{"key":"2023020112593619700_btw308-B18","doi-asserted-by":"crossref","first-page":"1084","DOI":"10.1126\/science.1233521","article-title":"Sex differences in the gut microbiome drive hormone-dependent regulation of autoimmunity","volume":"339","author":"Markle","year":"2013","journal-title":"Science"},{"key":"2023020112593619700_btw308-B19","doi-asserted-by":"crossref","first-page":"e1003531.","DOI":"10.1371\/journal.pcbi.1003531","article-title":"Waste not, want not: why rarefying microbiome data is inadmissible","volume":"10","author":"McMurdie","year":"2014","journal-title":"PLoS Comput. Biol"},{"key":"2023020112593619700_btw308-B20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1191\/1471082X05st084oa","article-title":"Random effect models for repeated measures of zero-inflated count data","volume":"5","author":"Min","year":"2005","journal-title":"Stat. Modell"},{"key":"2023020112593619700_btw308-B21","doi-asserted-by":"crossref","first-page":"1609","DOI":"10.1016\/j.csda.2011.10.005","article-title":"A general class of zero-or-one inflated beta regression models","volume":"56","author":"Ospina","year":"2012","journal-title":"Comput. Stat. Data Anal"},{"key":"2023020112593619700_btw308-B22","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1038\/nmeth.2658","article-title":"Differential abundance analysis for microbial marker-gene surveys","volume":"10","author":"Paulson","year":"2013","journal-title":"Nat. Methods"},{"key":"2023020112593619700_btw308-B23","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1089\/cmb.2015.0157","article-title":"Zero-inflated beta regression for differential abundance analysis with metagenomics data","volume":"23","author":"Peng","year":"2015","journal-title":"J. Comput. Biol"},{"key":"2023020112593619700_btw308-B24","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1038\/nature08821","article-title":"A human gut microbial gene catalogue established by metagenomic sequencing","volume":"464","author":"Qin","year":"2010","journal-title":"Nature"},{"key":"2023020112593619700_btw308-B25","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1038\/nature11450","article-title":"A metagenome-wide association study of gut microbiota in type 2 diabetes","volume":"490","author":"Qin","year":"2012","journal-title":"Nature"},{"key":"2023020112593619700_btw308-B26","doi-asserted-by":"crossref","first-page":"77.","DOI":"10.1186\/1471-2105-12-77","article-title":"proc: an open-source package for r and s+ to analyze and compare roc curves","volume":"12","author":"Robin","year":"2011","journal-title":"BMC Bioinformatics"},{"key":"2023020112593619700_btw308-B27","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1093\/biostatistics\/kxm030","article-title":"Small-sample estimation of negative binomial dispersion, with applications to sage data","volume":"9","author":"Robinson","year":"2007","journal-title":"Biostatistics"},{"key":"2023020112593619700_btw308-B28","doi-asserted-by":"crossref","first-page":"4.","DOI":"10.1186\/2049-2618-2-4","article-title":"The composition and stability of the vaginal microbiota of normal pregnant women is different from that of non-pregnant women","volume":"2","author":"Romero","year":"2014","journal-title":"Microbiome"},{"key":"2023020112593619700_btw308-B29","doi-asserted-by":"crossref","first-page":"e0137681.","DOI":"10.1371\/journal.pone.0137681","article-title":"Long term development of gut microbiota composition in atopic children: impact of probiotics","volume":"10","author":"Rutten","year":"2015","journal-title":"PloS One"},{"key":"2023020112593619700_btw308-B30","doi-asserted-by":"crossref","first-page":"508","DOI":"10.1038\/nature13398","article-title":"High-fat-diet-mediated dysbiosis promotes intestinal carcinogenesis independently of obesity","volume":"514","author":"Schulz","year":"2014","journal-title":"Nature"},{"key":"2023020112593619700_btw308-B31","doi-asserted-by":"crossref","first-page":"811","DOI":"10.1038\/nmeth.2066","article-title":"Metagenomic microbial community profiling using unique clade-specific marker genes","volume":"9","author":"Segata","year":"2012","journal-title":"Nat. Methods"},{"key":"2023020112593619700_btw308-B32","doi-asserted-by":"crossref","first-page":"e1003388.","DOI":"10.1371\/journal.pcbi.1003388","article-title":"Ecological modeling from time-series inference: insight into dynamics and stability of intestinal microbiota","volume":"9","author":"Stein","year":"2013","journal-title":"PLoS Comput. Biol"},{"key":"2023020112593619700_btw308-B33","doi-asserted-by":"crossref","first-page":"1027","DOI":"10.1038\/nature05414","article-title":"An obesity-associated gut microbiome with increased capacity for energy harvest","volume":"444","author":"Turnbaugh","year":"2006","journal-title":"Nature"},{"key":"2023020112593619700_btw308-B34","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1038\/nature06244","article-title":"The human microbiome project","volume":"449","author":"Turnbaugh","year":"2007","journal-title":"Nature"},{"key":"2023020112593619700_btw308-B35","doi-asserted-by":"crossref","first-page":"983","DOI":"10.1038\/ajg.2014.73","article-title":"Analyzing the human microbiome: a how to guide for physicians","volume":"109","author":"Tyler","year":"2014","journal-title":"Am. J. Gastroenterol"},{"key":"2023020112593619700_btw308-B36","doi-asserted-by":"crossref","first-page":"e20296\u2013e20296.","DOI":"10.1371\/journal.pone.0020296","article-title":"Application of two-part statistics for comparison of sequence variant counts","volume":"6","author":"Wagner","year":"2011","journal-title":"PloS One"},{"key":"2023020112593619700_btw308-B37","first-page":"e0118632\u2013e0118632.","article-title":"Longitudinal analysis of the premature infant intestinal microbiome prior to necrotizing enterocolitis: a case-control study","volume":"10","author":"Zhou","year":"2015","journal-title":"PloS One"}],"container-title":["Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/17\/2611\/49022795\/bioinformatics_32_17_2611.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article-pdf\/32\/17\/2611\/49022795\/bioinformatics_32_17_2611.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,18]],"date-time":"2024-06-18T19:17:52Z","timestamp":1718738272000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bioinformatics\/article\/32\/17\/2611\/2450750"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,5,14]]},"references-count":37,"journal-issue":{"issue":"17","published-print":{"date-parts":[[2016,9,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bioinformatics\/btw308","relation":{},"ISSN":["1367-4811","1367-4803"],"issn-type":[{"value":"1367-4811","type":"electronic"},{"value":"1367-4803","type":"print"}],"subject":[],"published-other":{"date-parts":[[2016,9,1]]},"published":{"date-parts":[[2016,5,14]]}}}