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HapNet: a new python package for automated population-aware haplotype network analysis and visualization
1Department of Biological, Chemical, and Environmental Sciences, Wheaton College Massachusetts, Norton, Massachusetts, USA.
Summary
HapNet is a new Python tool that creates haplotype networks to visualize DNA sequence relationships and population connectivity. It simplifies data analysis and generates publication-ready graphs and tables for population genetics research.
Area of Science:
- Population genetics
- Molecular ecology
- Phylogeography
Background:
- Haplotype networks are crucial for visualizing DNA sequence relationships and population connectivity.
- Current tools for constructing haplotype networks have limitations in usability and output.
Purpose of the Study:
- Introduce HapNet, an open-source Python package for creating population-aware, minimum-spanning-tree-based haplotype graphs.
- Provide a user-friendly and versatile tool for analyzing population genetic data.
Main Methods:
- HapNet collapses identical sequences into haplotypes from aligned FASTA files.
- It calculates Hamming distances and constructs Minimum Spanning Tree (MST)-based graphs.
- The tool generates visualizations with node size indicating haplotype frequency and pie charts showing population composition.
Main Results:
- HapNet produces publication-ready graphs and machine-readable tabular outputs.
- New features include metadata input, phased diploid sequence support, and individual genotype summaries.
- The package demonstrates utility with real and simulated datasets.
Conclusions:
- HapNet offers an efficient and comprehensive solution for haplotype network construction and visualization.
- The tool enhances the analysis of population structure and connectivity in genetic studies.
