Flexible cFDR

Flexible cFDR extends the conditional false-discovery rate framework to integrate auxiliary covariates from arbitrary continuous distributions into GWAS analyses to increase discovery power while controlling the false discovery rate.

Key Features:

• Extension of cFDR: Conditions GWAS p-values on auxiliary data and supports auxiliary covariates from arbitrary continuous distributions rather than requiring specific parametric forms.
• FDR control: Maintains control of the false discovery rate while leveraging auxiliary information to prioritize associations.
• Iterative application: Can be applied iteratively to incorporate multiple layers of auxiliary data for successive refinement of association signals.
• Increased sensitivity: Demonstrated increased sensitivity in simulation studies for detecting significant associations without compromising FDR control.
• Functional genomic integration: Accommodates diverse functional genomic annotations and other continuous auxiliary covariates to enhance SNP discovery.
• Empirical validation: Has been applied to an asthma GWAS and discoveries have been validated against larger independent datasets such as the UK Biobank.

Scientific Applications:

• GWAS discovery enhancement: Boosts power to detect genetic associations in genome-wide association studies by incorporating auxiliary continuous covariates.
• Integration of functional annotations: Enables combining functional genomic data with GWAS p-values to uncover associations tied to biological annotations.
• Pleiotropy-informed discovery: Leverages non-random SNP distributions and pleiotropy to improve detection of loci for complex traits.
• Validation and replication: Supports replication of findings in large cohorts such as the UK Biobank and application to trait-specific studies like asthma GWAS.

Methodology:

Conditions GWAS p-values on auxiliary continuous covariates; supports arbitrary continuous covariate distributions; can be applied iteratively to incorporate multiple auxiliary data layers; performance assessed via simulation studies and empirical application to an asthma GWAS with validation against UK Biobank.