# aPhyloGeo: a Python application for correlating genetic and climatic conditions

## TL;DR

aPhyloGeo is a Python tool that helps scientists study how genetic diversity relates to climate by integrating genetic and environmental data in a reproducible way.

## Contribution

aPhyloGeo introduces a novel, open-source Python application for analyzing correlations between genetic variation and environmental data using phylogenetic methods.

## Key findings

- aPhyloGeo enables the identification of mutation hotspots strongly associated with environmental variables.
- The tool supports reproducible and multicore processing workflows for phylogenetic and climatic data analysis.
- aPhyloGeo integrates multiple analytical steps including sequence alignment and statistical tests like the Mantel test.

## Abstract

Environmental variation and its influence on genetic diversity is a central topic in evolutionary biology and phylogeography. Accurate correlations between genetic and climatic datasets to understand the genetic adaptations of different species to specific environments. It requires integrated and reproducible workflows.

We developed aPhyloGeo, an open-source and multiplatform application implemented in Python, for investigating correlations between genetic variation and environmental data within a phylogenetic framework. The workflow integrates multiple analytical steps, including sequence alignment, sliding window phylogenetic inference, and statistical approaches such as the Mantel test and the Procrustean randomization test. These analyses enable the identification of mutation hotspots that exhibit strong associations with environmental variables. In addition, aPhyloGeo supports multicore data processing and provides a fully reproducible pipeline for evaluating localized relationships between genomic variation and climatic distributions.

aPhyloGeo is freely available on GitHub at: https://github.com/tahiri-lab/aPhyloGeo, as both a PyPI package and as Python scripts for Linux, macOS, and Windows.