A randomization-based causal inference framework for uncovering environmental exposure effects on human gut microbiota.
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| Title: | A randomization-based causal inference framework for uncovering environmental exposure effects on human gut microbiota. |
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| Authors: | Sommer AJ; Department of Statistics, Harvard University, Cambridge, Massachusetts, United States of America.; Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-University München, Munich, Germany.; Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany., Peters A; Institute for Medical Information Processing, Biometry, and Epidemiology, Faculty of Medicine, Ludwig-Maximilians-University München, Munich, Germany.; Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.; Department of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, United States of America., Rommel M; Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.; Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany., Cyrys J; Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany., Grallert H; Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany.; German Center for Diabetes Research (DZD), München-Neuherberg, Germany., Haller D; ZIEL - Institute for Food & Health, Technical University of Munich, Freising, Germany.; Chair of Nutrition and Immunology, Technical University of Munich, Freising, Germany., Müller CL; Institute of Computational Biology, Helmholtz Zentrum München, Neuherberg, Germany.; Department of Statistics, Ludwig-Maximilians-University München, Munich, Germany.; Center for Computational Mathematics, Flatiron Institute, New York City, New York, United States of America., Bind MC; Department of Statistics, Harvard University, Cambridge, Massachusetts, United States of America.; Biostatistics Center, Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, United States of America. |
| Source: | PLoS computational biology [PLoS Comput Biol] 2022 May 09; Vol. 18 (5), pp. e1010044. Date of Electronic Publication: 2022 May 09 (Print Publication: 2022). |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101238922 Publication Model: eCollection Cited Medium: Internet ISSN: 1553-7358 (Electronic) Linking ISSN: 1553734X NLM ISO Abbreviation: PLoS Comput Biol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1553-7358 |
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| DOI: | 10.1371/journal.pcbi.1010044 |
