PheWAS

PheWAS performs phenome-wide association analyses linking genetic variants to neuroimaging-derived phenotypes to identify gene–brain relationships.

Key Features:

• Unified genotype-to-phenotype strategy: Implements a genotype-to-phenotype framework to investigate associations between genetic factors and brain-wide imaging phenotypes.
• Scalable cloud-based computational infrastructure: Uses cloud computing resources to scale processing and data management for large-scale neuroimaging and genomic datasets.
• Advanced statistical methods: Performs association analysis with multiple-comparison correction and control of false discovery rate.
• Support for GWAS and case-control analyses: Supports large-scale case-control genome-wide association studies (GWAS) across imaging phenotypes.
• Multimodal association exploration: Enables systematic exploration of relationships between behavioral, environmental, or genetic factors and diverse neuroimaging markers.

Scientific Applications:

• Imaging PheWAS / GWAS: Identification of genetic variants linked to neurological and psychiatric disorders by integrating neuroimaging data with genomic information in PheWAS or GWAS frameworks.
• Variant-specific brain phenotype analysis: Characterization of variant effects such as apolipoprotein E (APOE) on brain morphological properties in cohorts like the Alzheimer's Disease Neuroimaging Initiative (ADNI).
• Large-cohort benchmarking: Processing and performance evaluation on large cohorts exemplified by UK Biobank for large-scale neuroimaging dataset analyses.

Methodology:

Systematic association testing between behavioral, environmental, or genetic variables and neuroimaging markers using association analysis and multiple-comparison correction controlling false discovery rate, executed on cloud-based scalable compute infrastructure.