A Bayesian method for detecting pairwise associations in compositional data

• Emma Schwager,

  Roles Conceptualization, Methodology, Software, Writing – original draft, Writing – review & editing

  Affiliations Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America

  http://orcid.org/0000-0002-7385-8994

  ⨯
• Himel Mallick,

  Roles Supervision, Writing – review & editing

  Affiliations Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America

  http://orcid.org/0000-0003-4956-2429

  ⨯
• Steffen Ventz,

  Roles Methodology, Supervision, Writing – review & editing

  Affiliations Department of Computer Science and Statistics, University of Rhode Island, Kingstown, Rhode Island, United States of America, Department of Biostatistics and Computational Biology, Dana-Farber Cancer Institute, Boston, Massachusetts, United States of America

  ⨯
• Curtis Huttenhower

  Roles Conceptualization, Funding acquisition, Methodology, Supervision, Writing – review & editing

  * E-mail: chuttenh@hsph.harvard.edu

  Affiliations Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, Massachusetts, United States of America, Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America

  ⨯