TRIO RVEMVS: A Bayesian framework for rare variant association analysis with expectation-maximization variable selection using family trio data

• Duo Yu,

  Roles Formal analysis, Investigation, Methodology, Software, Writing – original draft, Writing – review & editing

  Affiliation Division of Biostatistics, Data Science Institute, Medical College of Wisconsin, Milwaukee, Wisconsin, United States of America

  https://orcid.org/0000-0002-8988-1646

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• Matthew Koslovsky,

  Roles Conceptualization, Methodology, Writing – review & editing

  Affiliation Department of Statistics, Colorado State University, Fort Collins, Colorado, United States of America

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• Margaret C. Steiner,

  Roles Data curation, Investigation, Writing – review & editing

  Affiliation Department of Human Genetics, University of Chicago, Chicago, Illinois, United States of America

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• Kusha Mohammadi,

  Roles Data curation, Investigation, Writing – review & editing

  Affiliation Department of Biostatistics and Data Management, Regeneron Pharmaceuticals, Inc., Tarrytown, New York, United States of America

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• Chenguang Zhang,

  Roles Investigation, Writing – review & editing

  Affiliation Biostatistics and Research Decision Sciences, Merck & Co., Inc., North Wales, Pennsylvania, United States of America

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• Michael D. Swartz

  Roles Conceptualization, Funding acquisition, Investigation, Methodology, Resources, Supervision, Writing – original draft, Writing – review & editing

  * E-mail: michael.d.swartz@uth.tmc.edu

  Affiliation 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

  https://orcid.org/0000-0003-3953-8775

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