Genal

Genal consolidates SNP-level data handling, cleaning, clumping, Polygenic Risk Score computation, and Mendelian Randomization analyses into a single Python toolkit for genetic epidemiology.

Key Features:

• SNP-level data handling and cleaning: Processes and prepares genetic variant data for downstream analyses.
• Clumping: Performs linkage disequilibrium-based clumping of SNPs.
• Polygenic Risk Score computation: Calculates PRS from cleaned SNP-level data.
• Mendelian Randomization analyses: Implements MR methods including MR-PRESSO with parallel processing to reduce computational time.
• PLINK integration: Wraps around PLINK to eliminate the need for command-line interaction.

Scientific Applications:

• Polygenic Risk Score analysis: Quantifies cumulative genetic risk for traits or diseases using genome-wide association study summary statistics.
• Mendelian Randomization: Assesses causal relationships between exposures and outcomes using genetic variants as instrumental variables.
• Genetic epidemiology studies: Enables medical scientists to perform complex genetic association and causal inference analyses.

Methodology:

Genal wraps around PLINK for clumping and related operations, draws on concepts from several well-established tools for statistical techniques, and leverages parallel processing for MR methods including MR-PRESSO.