TRIO RVEMVS: A Bayesian framework for rare variant association analysis with expectation-maximization variable selection using family trio data.
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| Title: | TRIO RVEMVS: A Bayesian framework for rare variant association analysis with expectation-maximization variable selection using family trio data. |
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| Authors: | Yu D; Division of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America., Koslovsky M; Department of Statistics, Colorado State University, Fort Collins, Colorado, United States of America., Steiner MC; Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America., Mohammadi K; Department of Biostatistics and Data Management, Regeneron Pharmaceuticals, Inc., Tarrytown, New York, United States of America., Zhang C; Biostatistics and Research Decision Sciences, Merck & Co., Inc., North Wales, Pennsylvania, United States of America., Swartz MD; Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas, United States of America. |
| Source: | PloS one [PLoS One] 2024 Dec 04; Vol. 19 (12), pp. e0314502. Date of Electronic Publication: 2024 Dec 04 (Print Publication: 2024). |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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| ISSN: | 1932-6203 |
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| DOI: | 10.1371/journal.pone.0314502 |
