{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,4]],"date-time":"2026-10-04T03:28:25Z","timestamp":1791084505079,"version":"4.1.0"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1008913","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2021,10,5]],"date-time":"2021-10-05T00:00:00Z","timestamp":1633392000000}}],"reference-count":48,"publisher":"Public Library of Science (PLoS)","issue":"9","license":[{"start":{"date-parts":[[2021,9,13]],"date-time":"2021-09-13T00:00:00Z","timestamp":1631491200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000062","name":"National Institute of Diabetes and Digestive and Kidney Diseases","doi-asserted-by":"publisher","award":["R24DK110499"],"award-info":[{"award-number":["R24DK110499"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000060","name":"National Institute of Allergy and Infectious Diseases","doi-asserted-by":"publisher","award":["U19AI110820"],"award-info":[{"award-number":["U19AI110820"]}],"id":[{"id":"10.13039\/100000060","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100006754","name":"Army Research Laboratory","doi-asserted-by":"crossref","award":["W911NF-11-1-0473"],"award-info":[{"award-number":["W911NF-11-1-0473"]}],"id":[{"id":"10.13039\/100006754","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100008036","name":"Harvard Faculty of Arts and Sciences","doi-asserted-by":"crossref","award":["Dean\u2019s Competitive Fund"],"award-info":[{"award-number":["Dean\u2019s Competitive Fund"]}],"id":[{"id":"10.13039\/100008036","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>\n                    Many methods have been developed for statistical analysis of microbial community profiles, but due to the complex nature of typical microbiome measurements (e.g. sparsity, zero-inflation, non-independence, and compositionality) and of the associated underlying biology, it is difficult to compare or evaluate such methods within a single systematic framework. To address this challenge, we developed SparseDOSSA (Sparse Data Observations for the Simulation of Synthetic Abundances): a statistical model of microbial ecological population structure, which can be used to parameterize real-world microbial community profiles and to simulate new, realistic profiles of known structure for methods evaluation. Specifically, SparseDOSSA\u2019s model captures marginal microbial feature abundances as a zero-inflated log-normal distribution, with additional model components for absolute cell counts and the sequence read generation process, microbe-microbe, and microbe-environment interactions. Together, these allow fully known covariance structure between synthetic features (i.e. \u201ctaxa\u201d) or between features and \u201cphenotypes\u201d to be simulated for method benchmarking. Here, we demonstrate SparseDOSSA\u2019s performance for 1) accurately modeling human-associated microbial population profiles; 2) generating synthetic communities with controlled population and ecological structures; 3) spiking-in true positive synthetic associations to benchmark analysis methods; and 4) recapitulating an end-to-end mouse microbiome feeding experiment. Together, these represent the most common analysis types in assessment of real microbial community environmental and epidemiological statistics, thus demonstrating SparseDOSSA\u2019s utility as a general-purpose aid for modeling communities and evaluating quantitative methods. An open-source implementation is available at\n                    <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" ext-link-type=\"uri\" xlink:href=\"http:\/\/huttenhower.sph.harvard.edu\/sparsedossa2\" xlink:type=\"simple\">http:\/\/huttenhower.sph.harvard.edu\/sparsedossa2<\/jats:ext-link>\n                    .\n                  <\/jats:p>","DOI":"10.1371\/journal.pcbi.1008913","type":"journal-article","created":{"date-parts":[[2021,9,13]],"date-time":"2021-09-13T13:33:46Z","timestamp":1631540026000},"page":"e1008913","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":76,"title":["A statistical model for describing and simulating microbial community 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