A Julia package providing core utilities for manipulating, comparing, and analyzing phylogenetic trees and networks.
PhyloNetworks is a Julia package that provides core utilities for working with phylogenetic trees and networks, which model evolutionary relationships among organisms. It solves the need for efficient manipulation, comparison, and analysis of complex phylogenetic data structures, serving as a foundational tool for evolutionary biology research.
Bioinformaticians, evolutionary biologists, and researchers in computational biology who need to analyze phylogenetic relationships using Julia. It's also for developers building specialized phylogenetic tools that require a reliable core library.
Developers choose PhyloNetworks because it offers a high-performance, modular core written in Julia, specifically designed for phylogenetic networks with robust utilities for network manipulation and comparison. Its integration with the JuliaPhylo ecosystem allows for seamless extension and specialization.
PhyloNetworks: a julia package with utilities for phylogenetic networks
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Designed as a stable, efficient core package that other specialized phylogenetic packages in the JuliaPhylo ecosystem depend on, promoting modularity and interoperability for evolutionary biology research.
Provides extensive utilities for manipulating phylogenetic networks, including re-rooting, pruning taxa, and transforming networks with semidirected nearest-neighbor interchange (sNNI), as highlighted in the README.
Includes network traversal routines that enable efficient data processing and algorithm implementation, optimizing performance for large phylogenetic datasets.
Supports reading and writing phylogenies in (extended) Newick format, a standard in the field, ensuring compatibility with other phylogenetic tools and data sources.
Version 0.17 introduced major breaking changes from previous versions, including renamed methods and moved functionalities to other packages, which can disrupt existing codebases and require significant migration effort.
Visualization capabilities are not included; users must integrate with separate packages like PhyloPlots for graphical output, adding complexity and dependency management to the workflow.
Heavily tied to the Julia programming language and its ecosystem, making it less accessible for teams not invested in Julia or preferring more established phylogenetic tools in other languages like R or Python.