An improved statistical method to identify chemical-genetic interactions by exploiting concentration-dependence

• Esha Dutta,

  Roles Formal analysis, Methodology, Software, Writing – original draft

  Affiliation Department of Computer Science, Texas A&M University, College Station, TX, United States of America

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• Michael A. DeJesus,

  Roles Methodology, Writing – review & editing

  Affiliation Laboratory of Host-Pathogen Biology, The Rockefeller University, New York, NY, United States of America

  https://orcid.org/0000-0003-3867-0299

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• Nadine Ruecker,

  Roles Methodology, Writing – review & editing

  Affiliation Department of Microbiology and Immunology, Weill Cornell Medical College, New York, NY, United States of America

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• Anisha Zaveri,

  Roles Methodology, Writing – review & editing

  Affiliation Department of Microbiology and Immunology, Weill Cornell Medical College, New York, NY, United States of America

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• Eun-Ik Koh,

  Roles Data curation, Methodology, Writing – review & editing

  Affiliation Department of Microbiology & Physiological Systems, University of Massachusetts Medical School, Worchester, MA, United States of America

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• Christopher M. Sassetti,

  Roles Writing – review & editing

  Affiliation Department of Microbiology & Physiological Systems, University of Massachusetts Medical School, Worchester, MA, United States of America

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• Dirk Schnappinger,

  Roles Funding acquisition, Writing – review & editing

  Affiliation Department of Microbiology and Immunology, Weill Cornell Medical College, New York, NY, United States of America

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• Thomas R. Ioerger

  Roles Conceptualization, Formal analysis, Methodology, Writing – original draft

  * E-mail: ioerger@cs.tamu.edu

  Affiliation Department of Computer Science, Texas A&M University, College Station, TX, United States of America

  https://orcid.org/0000-0001-8702-9102

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