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OpenMendel: a cooperative programming project for statistical genetics

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Abstract

Statistical methods for genome-wide association studies (GWAS) continue to improve. However, the increasing volume and variety of genetic and genomic data make computational speed and ease of data manipulation mandatory in future software. In our view, a collaborative effort of statistical geneticists is required to develop open source software targeted to genetic epidemiology. Our attempt to meet this need is called the OpenMendel project (https://openmendel.github.io). It aims to (1) enable interactive and reproducible analyses with informative intermediate results, (2) scale to big data analytics, (3) embrace parallel and distributed computing, (4) adapt to rapid hardware evolution, (5) allow cloud computing, (6) allow integration of varied genetic data types, and (7) foster easy communication between clinicians, geneticists, statisticians, and computer scientists. This article reviews and makes recommendations to the genetic epidemiology community in the context of the OpenMendel project.

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  1. Hua Zhou and Janet S. Sinsheimer authors contributed equally.

Authors and Affiliations

  1. Department of Biostatistics, UCLA Fielding School of Public Health, Los Angeles, USA

    Hua Zhou, Christopher A. German, Sarah S. Ji & Juhyun Kim

  2. Department of Human Genetics, David Geffen School of Medicine at UCLA, Los Angeles, USA

    Janet S. Sinsheimer, Jeanette C. Papp & Eric M. Sobel

  3. Department of Statistics, University of Wisconsin, Madison, USA

    Douglas M. Bates

  4. Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, USA

    Benjamin B. Chu & Kenneth Lange

  5. Department of Medicine, University of California, San Francisco, USA

    Kevin L. Keys

  6. Department of Statistics, Seoul National University, Seoul, South Korea

    Seyoon Ko

  7. Departments of Statistics and Computer Science, University of California, Riverside, USA

    Gordon D. Mosher

  8. Department of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson, USA

    Jing Zhai & Jin J. Zhou

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NIH Grants R01-GM53275, R01-HG006139, R01-GM105785, R01-HL135156 and T32-HG002536; NSF grant DMS-1052210; the UCSF Bakar Computational Health Sciences Institute; the UC Berkeley Institute for Data Sciences as part of the Moore-Sloan Data Sciences Environment Initiative; and the 2018 Google Summer of Code.

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Zhou, H., Sinsheimer, J.S., Bates, D.M. et al. OpenMendel: a cooperative programming project for statistical genetics. Hum Genet 139, 61–71 (2020). https://doi.org/10.1007/s00439-019-02001-z

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