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Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics

Citations

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Cited by:

  1. Zhao, Xin & Zhang, Jingru & Lin, Wei, 2023. "Clustering multivariate count data via Dirichlet-multinomial network fusion," Computational Statistics & Data Analysis, Elsevier, vol. 179(C).
  2. Einar E. Birkeland & Ane S. Kværner & Ekaterina Avershina & Cecilie Bucher-Johannessen & Vahid Bemanian & Hege S. Blix & Anette Hjartåker & Willem M. de Vos & Giske Ursin & Geir Hoff & Kristin R. Rand, 2026. "Microbiome signatures for detection of colorectal lesions in population-based FIT screening," Nature Communications, Nature, vol. 17(1), pages 1-17, December.
  3. Abdolnasser Sadeghkhani, 2026. "Bayesian Poisson‐Lognormal Regression With Compositional Effect Shares for Multivariate Count Data," Environmetrics, John Wiley & Sons, Ltd., vol. 37(4), May.
  4. Binhuan Wang & Lanqiu Yao & Jiyuan Hu & Huilin Li, 2023. "A New Algorithm for Convex Biclustering and Its Extension to the Compositional Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 15(1), pages 193-216, April.
  5. Yaru Song & Hongyu Zhao & Tao Wang, 2020. "An adaptive independence test for microbiome community data," Biometrics, The International Biometric Society, vol. 76(2), pages 414-426, June.
  6. Julien Tap & Franck Lejzerowicz & Aurélie Cotillard & Matthieu Pichaud & Daniel McDonald & Se Jin Song & Rob Knight & Patrick Veiga & Muriel Derrien, 2023. "Global branches and local states of the human gut microbiome define associations with environmental and intrinsic factors," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
  7. Pratheepa Jeganathan & Susan P. Holmes, 2021. "A Statistical Perspective on the Challenges in Molecular Microbial Biology," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 26(2), pages 131-160, June.
  8. Achal Dhariwal & Polona Rajar & Gabriela Salvadori & Heidi Aarø Åmdal & Dag Berild & Ola Didrik Saugstad & Drude Fugelseth & Gorm Greisen & Ulf Dahle & Kirsti Haaland & Fernanda Cristina Petersen, 2024. "Prolonged hospitalization signature and early antibiotic effects on the nasopharyngeal resistome in preterm infants," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
  9. Patrick LeBlanc & Li Ma, 2023. "Microbiome subcommunity learning with logistic‐tree normal latent Dirichlet allocation," Biometrics, The International Biometric Society, vol. 79(3), pages 2321-2332, September.
  10. Juan Xie & Hyeongseon Jeon & Gang Xin & Qin Ma & Dongjun Chung, 2023. "LRT: Integrative analysis of scRNA-seq and scTCR-seq data to investigate clonal differentiation heterogeneity," PLOS Computational Biology, Public Library of Science, vol. 19(7), pages 1-17, July.
  11. Emma M. Koff & Debbie Baarle & Marlies A. Houten & Marta Reyman & Guy A. M. Berbers & Femke Ham & Mei Ling J. N. Chu & Elisabeth A. M. Sanders & Debby Bogaert & Susana Fuentes, 2022. "Mode of delivery modulates the intestinal microbiota and impacts the response to vaccination," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
  12. Shaikh Mateen R. & Beyene Joseph, 2017. "Statistical models and computational algorithms for discovering relationships in microbiome data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 16(1), pages 1-12, March.
  13. Mahbaneh Eshaghzadeh Torbati & Makedonka Mitreva & Vanathi Gopalakrishnan, 2016. "Application of Taxonomic Modeling to Microbiota Data Mining for Detection of Helminth Infection in Global Populations," Data, MDPI, vol. 1(3), pages 1-14, December.
  14. Zhiwei Qin & John Bowman & Jagtej Bewli, 2018. "A Bayesian framework for large-scale geo-demand estimation in on-line retailing," Annals of Operations Research, Springer, vol. 263(1), pages 231-245, April.
  15. Laura Anderlucci & Cinzia Viroli, 2020. "Mixtures of Dirichlet-Multinomial distributions for supervised and unsupervised classification of short text data," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 14(4), pages 759-770, December.
  16. Wangshu Tu & Sanjeena Subedi, 2023. "Logistic Normal Multinomial Factor Analyzers for Clustering Microbiome Data," Journal of Classification, Springer;The Classification Society, vol. 40(3), pages 638-667, November.
  17. Georgios D. Kitsios & Khaled Sayed & Adam Fitch & Haopu Yang & Noel Britton & Faraaz Shah & William Bain & John W. Evankovich & Shulin Qin & Xiaohong Wang & Kelvin Li & Asha Patel & Yingze Zhang & Jos, 2024. "Longitudinal multicompartment characterization of host-microbiota interactions in patients with acute respiratory failure," Nature Communications, Nature, vol. 15(1), pages 1-18, December.
  18. Mishra, Aditya & Müller, Christian L., 2022. "Robust regression with compositional covariates," Computational Statistics & Data Analysis, Elsevier, vol. 165(C).
  19. Sanjeena Subedi & Drew Neish & Stephen Bak & Zeny Feng, 2020. "Cluster analysis of microbiome data by using mixtures of Dirichlet–multinomial regression models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 69(5), pages 1163-1187, November.
  20. Gallopin Mélina & Celeux Gilles & Jaffrézic Florence & Rau Andrea, 2015. "A model selection criterion for model-based clustering of annotated gene expression data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(5), pages 413-428, November.
  21. Carsten Eriksen & Ioanna Chatzigiannidou & Rasmus Kaae Dehli & Pi Lærke Johansen & Thomas Meinertz Dantoft & Oluf Pedersen & Torben Hansen & Allan Linneberg & Tine Jess & Kristine Højgaard Allin & Tor, 2026. "Gut microbiota composition outperforms chronological age in predicting systemic inflammation and incident disease risk," Nature Communications, Nature, vol. 17(1), pages 1-12, December.
  22. Sean M Gibbons & Sean M Kearney & Chris S Smillie & Eric J Alm, 2017. "Two dynamic regimes in the human gut microbiome," PLOS Computational Biology, Public Library of Science, vol. 13(2), pages 1-20, February.
  23. Tu, Wangshu & Browne, Ryan & Subedi, Sanjeena, 2024. "A mixture of logistic skew-normal multinomial models," Computational Statistics & Data Analysis, Elsevier, vol. 196(C).
  24. Doris Vandeputte & Lindsey Commer & Raul Y. Tito & Gunter Kathagen & João Sabino & Séverine Vermeire & Karoline Faust & Jeroen Raes, 2021. "Temporal variability in quantitative human gut microbiome profiles and implications for clinical research," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
  25. Kihyun Lee & Sebastien Raguideau & Kimmo Sirén & Francesco Asnicar & Fabio Cumbo & Falk Hildebrand & Nicola Segata & Chang-Jun Cha & Christopher Quince, 2023. "Population-level impacts of antibiotic usage on the human gut microbiome," Nature Communications, Nature, vol. 14(1), pages 1-19, December.
  26. Carl M. Kobel & Andy Leu & Arturo Vera-Ponce de León & Ove Øyås & Wanxin Lai & Ianina Altshuler & Live H. Hagen & Rasmus D. Wollenberg & Mads T. Søndergaard & Cassie R. Bakshani & William G. T. Willat, 2025. "Protozoal populations drive system-wide variation in the rumen microbiome," Nature Communications, Nature, vol. 16(1), pages 1-17, December.
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