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

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Název: aPhyloGeo: a Python application for correlating genetic and climatic conditions.
Autoři: Galaz, Ana Laura Chenoweth, Tahiri, Nadia
Zdroj: Bioinformatics; Nov2025, Vol. 41 Issue 11, p1-5, 5p
Témata: GENETIC variation, PHYLOGEOGRAPHY, GENETIC mutation, PYTHON programming language, GEOSPATIAL data, ELECTRONIC data processing, CLIMATE change
Abstrakt: Motivation 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. Results 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. Availability and implementation 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. [ABSTRACT FROM AUTHOR]
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Databáze: Complementary Index
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Abstrakt:Motivation 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. Results 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. Availability and implementation 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. [ABSTRACT FROM AUTHOR]
ISSN:13674803
DOI:10.1093/bioinformatics/btaf574