GWASLab Agent
Project description
GWASLab-Agent
GWASLab-Agent is an LLM-powered framework for automated GWAS summary statistics processing, quality control, transformation, and visualization.
It extends the original GWASLab Python package with intelligent planning, multi-step workflow generation, and agent-driven execution.
GWASLab-Agent is designed to serve as an autonomous GWAS assistant, capable of interpreting user instructions, planning complex operations, managing file paths, and producing publication-ready summaries and figures.
Installation
- Create a new environment (recommended)
# Create a clean environment with Python 3.12
conda create -n gwaslab-agent python=3.12
# Activate it
conda activate gwaslab-agent
- Install GWASLab and GWASLab-Agent
pip install gwaslab
pip install gwaslab_agent
Design of GWASLab-Agent
SmartSumstats Object
At the core of GWASLab-Agent is the SmartSumstats object — an LLM-enhanced wrapper around gl.Sumstats.
It integrates five coordinated sub-agents:
- Loader — detects file formats, parses paths, handles chromosome patterns
- Planner — constructs optimal multi-step workflows
- Worker — executes tasks, QC steps, and visualizations
- PathManager — manages input/output paths and reference resources
- Summarizer — generates structured summaries and Methods-section text
Together, these sub-agents enable fully automated GWAS workflows with minimal user input.
Citation
(Coming soon — please cite GWASLab and GWASLab-Agent once the corresponding manuscripts or preprints are available.)
Project details
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