agricola

agricola

agricola is a command-line tool and Python package for conducting genome-wide association studies (GWAS) in admixed populations. Inspired by regenie and Tractor, agricola provides a scalable, local-ancestry–aware framework that handles relatedness, population structure, and ancestry effect heterogeneity. Agricola is highly computationally efficient and can be run on GPU, CPU, or TPU compute environments.

---

Documentation

Full documentation, including examples, methods description, and details can be found here: https://frankp-0.github.io/agricola

Why agricola?

Admixed individuals have unique LD patterns that can improve signal localization and improve power for population-specific causal variants. However, standard GWAS tools fail to adjust for local ancestry or model effect heterogeneity in admixed individuals.

Tools like Tractor address this gap by performing single-variant association tests with explicit local ancestry adjustment. agricola follows the same conceptual approach but uses whole genome regression to correct for sample relatedness. Other features include:

• Accelerated linear algebra via JAX
• CUDA GPU, TPU, or CPU support for flexible compute environments
• Fast local ancestry queries using lanctools
• Efficient multi-phenotype modeling
• Hypothesis testing for ancestry effect heterogeneity

---

Installation

Requirements: Python 3.12+

Install via pip:

pip install agricola

For GPU or TPU support:

pip install agricola[cuda]

pip install agricola[tpu]