Federated GWAS workflow
Coordinate quality control, kinship analysis, local regression filtering, and final association analysis across multiple centers.
Start from the task in front of you
Core documentation paths are split by workflow so setup, examples, and reference material stay easy to scan.
Pre-requisites
Set up Python, PLINK, Flower, and the required runtime tools.
Local Simulation
Run the default tiny correctness experiment from data generation to evaluation.
Examples
Browse tiny correctness, performance small, and 1000 Genomes workflows.
API Reference
Look up Flower run config, YAML schema, output files, and Python entry points.
Built for research operations
The documentation follows the repository structure so researchers can move from setup to pipeline internals without switching mental models.
Privacy-aware aggregation
Use ECC key exchange, pairwise PRG masking, and deterministic ID anonymization to reduce raw data exposure during collaboration.
Experiment-ready layout
Run repeatable Flower simulation and local-deployment experiments with scenario-specific configs, logs, and result directories.