bio-workflows-causal-genomics-pipeline

What problem does it solve?

End-to-end post-GWAS causal inference pipeline that connects GWAS summary statistics to causal effects, enabling researchers to identify exposures, shared variants, and mediating mechanisms through a structured, reproducible workflow.

Core Features & Use Cases

• Instrument selection and Mendelian randomization analysis (IVW, MR-Egger, weighted median) to triangulate causal effects.
• Comprehensive sensitivity analyses (MR-PRESSO, Egger intercept, Steiger directionality) to assess pleiotropy and bias.
• Colocalization and fine-mapping to pinpoint shared causal variants at loci of interest.
• Mediation analysis via multivariable MR to evaluate indirect pathways and mediators.
• End-to-end workflow examples for typical post-GWAS questions (e.g., BMI and cardiovascular outcomes).

Quick Start

Run the full causal inference pipeline on your GWAS summary statistics to obtain triangulated causal evidence.