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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

  1. 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
  1. 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.)

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