Submitted by ja607 on
Title | PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection. |
Publication Type | Journal Article |
Year of Publication | 2020 |
Authors | Tang, Z-Z, Sliwoski, GR, Chen, G, Jin, B, Bush, WS, Li, B, Capra, JA |
Journal | Genome Biol |
Volume | 21 |
Issue | 1 |
Pagination | 217 |
Date Published | 2020 08 26 |
ISSN | 1474-760X |
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. |
DOI | 10.1186/s13059-020-02121-0 |
Alternate Journal | Genome Biol |
PubMed ID | 32847609 |
PubMed Central ID | PMC7448521 |
Grant List | R35GM127087 / NH / NIH HHS / United States R35 GM127087 / GM / NIGMS NIH HHS / United States T15LM007450 / NH / NIH HHS / United States R01GM126249 / NH / NIH HHS / United States 1U01HG009086-01 / NH / NIH HHS / United States |