You are here

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

TitlePSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection.
Publication TypeJournal Article
Year of Publication2020
AuthorsTang Z-Z, Sliwoski GR, Chen G, Jin B, Bush WS, Li B, Capra JA
JournalGenome Biol
Volume21
Issue1
Pagination217
Date Published2020 08 26
ISSN1474-760X
KeywordsAlgorithms, Alzheimer Disease, Genetic Association Studies, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Humans, Lipids, Models, Genetic, Phenotype, Proteins
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.

DOI10.1186/s13059-020-02121-0
Pubmed Linkhttps://www.ncbi.nlm.nih.gov/pubmed/32847609?dopt=Abstract
page_expoExternal
Alternate JournalGenome Biol
PubMed ID32847609
PubMed Central IDPMC7448521
Grant ListR35GM127087 / 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

Theme by Danetsoft and Danang Probo Sayekti inspired by Maksimer