COVID-GWAB

COVID-GWAB enhances prioritization of host genes associated with COVID-19 by applying network boosting to GWAS summary statistics using the HumanNet co-functional human gene network.

Key Features:

• Integration of functional interactions: Enhances original GWAS signals by incorporating molecular interaction information from gene networks to amplify weak association signals.
• Use of HumanNet: Leverages the HumanNet co-functional human gene network to reprioritize candidate host genes based on interactome neighbor signals.
• Input summary statistics: Processes GWAS summary statistics from the COVID-19 Host Genetics Initiative (HGI) or user-provided datasets.
• Pre-processed HGI data: Includes pre-processed summary statistics from HGI releases 5, 6, and 7 for analysis.
• Augmented GWAS outputs: Produces summaries of boosted GWAS signals and reprioritized candidate genes informed by network propagation.
• Multi-evidence evaluation: Evaluates candidate genes using appearance frequency in COVID-19 literature, integration with single-cell transcriptome data, and pathway association analyses.
• Independent dataset evaluation: Enables assessment of boosted results using independent datasets to corroborate associations.

Scientific Applications:

• Host genetics discovery: Identification and prioritization of host genes associated with COVID-19 susceptibility and disease response.
• Therapeutic target nomination: Prioritization of candidate genes for downstream experimental validation or therapeutic targeting.
• GWAS signal recovery: Amplification and reinterpretation of weak or subthreshold GWAS signals from studies with limited statistical power.
• Mechanistic interpretation: Integration with single-cell transcriptome and pathway data to support mechanistic hypotheses about molecular contributors to COVID-19 outcomes.

Methodology:

Accepts GWAS summary statistics from the COVID-19 HGI or user-provided datasets and applies network boosting using the HumanNet co-functional gene network to reprioritize genes based on functional interactions.