Demographic Modeling of Admixed Latin American Populations from Whole Genomes

This repository contains the code and data used in our study, "Demographic Modeling of Admixed Latin American Populations from Whole Genomes". In this study, we developed novel demographic models that capture the complex evolutionary history of Latin American populations, which have been shaped by both recent admixture and deeper-in-time demographic events. Our models improve upon existing approaches to infer patterns of genetic variation in admixed populations, and can be a valuable resource for improving genomic studies and prediction in these populations.

Data

We used high-coverage whole genome data from Indigenous American ancestries in present-day Mexico, as well as existing genomes from across Latin America, to infer multiple demographic models. The data used in our study is available from public repositories and is described in the paper.

Code

The code used to analyze the data and infer demographic models is provided in this repository. We used a combination of analyses of allele frequencies and ancestry tract length distributions to develop our models. The code is written in Python and makes use of several open-source libraries, including demes, msprime, moments, tracs, and scikit-allel.

Demographic Models

We provide the inferred demographic models in the models directory, in the demes format. The models include:

• m1-out-of-africa.yml: Four populations out of Africa.
• m2-Mexico-admixture.yml: Admixture in Mexico.
• m3-Colombia-admixture.yml: Admixture in Colombia.
• m4-Peru-admixture.yml: Admixture in Peru.
• m5-PuertoRico-admixture.yml: Admixture in Puerto Rico.
• m6-All-admixture.yml: Admixture in Latin American populations.

Usage

To use the Models, you can install the demes library and load the models using the demes.load function.

import demes

model = demes.load("models/m1-out-of-africa.yml")

Citation

If you use any part of this code or the inferred models in your work, please cite our paper:

@article{medina2023demographic,
  title={Demographic Modeling of Admixed Latin American Populations from Whole Genomes},
  author={Medina-Munoz, Santiago G and Ortega-Del Vecchyo, Diego and Cruz-Hervert, Luis Pablo and Ferreyra-Reyes, Leticia and Garcia-Garcia, Lourdes and Moreno-Estrada, Andres and Ragsdale, Aaron},
  journal={bioRxiv},
  pages={2023--03},
  year={2023},
  publisher={Cold Spring Harbor Laboratory}
}

Please let us know if you have any questions or issues with the code or data provided in this repository.