Treffer: Phylo-rs: an extensible phylogenetic analysis library in rust.

Title:
Phylo-rs: an extensible phylogenetic analysis library in rust.
Authors:
Vijendran S; Department of Computer Science, Iowa State University, Ames, IA, 50011, USA. sriramv@iastate.edu., Anderson T; National Animal Disease Center, Agricultural Research Service, United States Department of Agriculture, Ames, IA, 50010, USA., Markin A; National Animal Disease Center, Agricultural Research Service, United States Department of Agriculture, Ames, IA, 50010, USA., Eulenstein O; Department of Computer Science, Iowa State University, Ames, IA, 50011, USA. oeulenst@iastate.edu.
Source:
BMC bioinformatics [BMC Bioinformatics] 2025 Jul 29; Vol. 26 (1), pp. 197. Date of Electronic Publication: 2025 Jul 29.
Publication Type:
Journal Article
Language:
English
Journal Info:
Publisher: BioMed Central Country of Publication: England NLM ID: 100965194 Publication Model: Electronic Cited Medium: Internet ISSN: 1471-2105 (Electronic) Linking ISSN: 14712105 NLM ISO Abbreviation: BMC Bioinformatics Subsets: MEDLINE
Imprint Name(s):
Original Publication: [London] : BioMed Central, 2000-
MeSH Terms:
Phylogeny* , Software* , Computational Biology*/methods, Algorithms ; Animals ; Swine
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Grant Information:
75N93021C00015 United States AI NIAID NIH HHS; 5030-32000-231-000-D Agricultural Research Service; 5030-32000-231-111-I Agricultural Research Service; 3022-32000-018-017-S Agricultural Research Service
Contributed Indexing:
Keywords: Library; Phylogenetics; Rust; WebAssembly
Entry Date(s):
Date Created: 20250730 Date Completed: 20250730 Latest Revision: 20250802
Update Code:
20250802
PubMed Central ID:
PMC12309125
DOI:
10.1186/s12859-025-06234-w
PMID:
40731312
Database:
MEDLINE

Weitere Informationen

Background: The advent of next-generation and long-read sequencing technologies has provided an ever-increasing wealth of phylogenetic data that require specially designed algorithms to decipher the underlying evolutionary relationships. As large-scale data become increasingly accessible, there is a concomitant need for efficient computational libraries that facilitate the development and dissemination of specialized algorithms for phylogenetic comparative biology.
Results: We introduce Phylo-rs: a fast, extensible, general-purpose library for phylogenetic analysis and inference written in the Rust programming language. Phylo-rs leverages a combination of speed, memory-safety, and native WebAssembly support offered by Rust to provide a robust set of memory-efficient data structures and elementary phylogenetic algorithms. Phylo-rs focuses on the efficient and convenient deployment of software aimed at large-scale phylogenetic analysis and inference. Scalability analysis against popular libraries shows that Phylo-rs performs comparably or better on key algorithms. We utilized it to assess the phylogenetic diversity of influenza A virus in swine, identifying virus groups that are undergoing evolutionary expansion that could be targeted for control through multivalent vaccines. Additionally, we used Phylo-rs to enhance phylogenetic inference by visualizing tree space from Markov chain Monte Carlo (MCMC) Bayesian analysis, efficiently computing approximately five billion tree pair distances to evaluate convergence and select MCMC runs for genomic epidemiology.
Conclusion: Phylo-rs enables the design and implementation of cutting-edge software for phylogenetic analysis, thereby facilitating the application and dissemination of theoretical advancements in biology. Phylo-rs is available under an open-source license on GitHub at https://github.com/sriram98v/phylo-rs , with documentation available at https://docs.rs/phylo/latest/phylo/ .
(© 2025. The Author(s).)

Declarations. Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.