PSCAN: Spatial scan tests guided by protein structures improve complex disease gene discovery and signal variant detection.
Zheng-Zheng TangGregory R SliwoskiGuanhua ChenBowen JinWilliam S BushBingshan LiJohn A CapraPublished in: Genome biology (2020)
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.
Keyphrases
- copy number
- genome wide
- protein protein
- computed tomography
- high resolution
- small molecule
- electronic health record
- magnetic resonance imaging
- big data
- gene expression
- magnetic resonance
- dna methylation
- machine learning
- cognitive decline
- deep learning
- high throughput
- artificial intelligence
- genome wide identification
- loop mediated isothermal amplification