Genome Biology (Aug 2020)

PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection

  • Zheng-Zheng Tang,
  • Gregory R. Sliwoski,
  • Guanhua Chen,
  • Bowen Jin,
  • William S. Bush,
  • Bingshan Li,
  • John A. Capra

DOI
https://doi.org/10.1186/s13059-020-02121-0
Journal volume & issue
Vol. 21, no. 1
pp. 1 – 25

Abstract

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Abstract Germline disease-causing variants are generally more spatially clustered in protein 3-dimensional structures than benign variants. Motivated by this tendency, we develop a fast and powerful protein-structure-based scan (PSCAN) approach for evaluating gene-level associations with complex disease and detecting signal variants. We validate PSCAN’s performance on synthetic data and two real data sets for lipid traits and Alzheimer’s disease. Our results demonstrate that PSCAN performs competitively with existing gene-level tests while increasing power and identifying more specific signal variant sets. Furthermore, PSCAN enables generation of hypotheses about the molecular basis for the associations in the context of protein structures and functional domains.

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