diff --git a/joss.06943/paper.jats/10.21105.joss.06943.jats b/joss.06943/paper.jats/10.21105.joss.06943.jats new file mode 100644 index 0000000000..e3fad9dcbf --- /dev/null +++ b/joss.06943/paper.jats/10.21105.joss.06943.jats @@ -0,0 +1,1525 @@ + + +
+ + + + +Journal of Open Source Software +JOSS + +2475-9066 + +Open Journals + + + +6943 +10.21105/joss.06943 + +DendroPy 5: a mature Python library for phylogenetic +computing + + + +https://orcid.org/0000-0003-4726-4479 + +Moreno +Matthew Andres + + + + + + +https://orcid.org/0000-0001-5575-0536 + +Holder +Mark T. + + + + + +https://orcid.org/0000-0002-9222-9608 + +Sukumaran +Jeet + + + + + +Department of Ecology and Evolutionary Biology, University +of Michigan, Ann Arbor, MI, United States of America + + + + +Center for the Study of Complex Systems, University of +Michigan, Ann Arbor, MI, United States of America + + + + +Michigan Institute for Data and AI in Society, University +of Michigan, Ann Arbor, MI, United States of America + + + + +Department of Ecology and Evolutionary Biology, University +of Kansas, Lawrence, KS, United States of America + + + + +Biodiversity Institute, University of Kansas, Lawrence, KS, +United States of America + + + + +Department of Biology, San Diego State University, San +Diego, CA, United States of America + + + + +19 +5 +2024 + +9 +101 +6943 + +Authors of papers retain copyright and release the +work under a Creative Commons Attribution 4.0 International License (CC +BY 4.0) +2022 +The article authors + +Authors of papers retain copyright and release the work under +a Creative Commons Attribution 4.0 International License (CC BY +4.0) + + + +Python +phylogenetics +phylogeny +phylogenies +phylogeography +biology +evolution +evolutionary biology +systematics +coalescent +population +genetics +phyloinformatics +bioinformatics + + + + + + Summary +

Modern bioinformatics has unlocked remarkable insight into the + composition, structure, and history of the natural world around us. + Arguably, the central pillar of bioinformatics is phylogenetics — the + study of hereditary relatedness among organisms. Insights from + phylogenetic analysis have touched nearly every corner of biology. + Examples range across natural history + (Title + et al., 2024), population genetics and phylogeography + (Knowles + & Maddison, 2002), conservation biology + (Faith, + 1992), public health + (Giardina + et al., 2017; + Voznica + et al., 2022), medicine + (Kim + et al., 2006; + Lewinsohn + et al., 2023), in vivo and in + silico experimental evolution + (Lenski + et al., 2003; + Moreno + et al., 2023; + Rozen + et al., 2005), application-oriented evolutionary algorithms + (Hernandez + et al., 2022; + Lalejini + et al., 2024; + Shahbandegan + et al., 2022), and beyond.

+

High-throughput genetic and phenotypic data has realized + groundbreaking results, in large part, through conjunction with + open-source software used to process and analyze it. Indeed, the + preceding decades have ushered in a flourishing ecosystem of + bioinformatics software applications and libraries. Over the course of + its nearly fifteen-year history, the DendroPy library for phylogenetic + computation in Python has established a generalist niche in serving + the bioinformatics community + (Sukumaran + & Holder, 2010). Here, we report on the recent major + release of the library, DendroPy version 5. The software release + represents a major milestone in transitioning the library to a + sustainable long-term development and maintenance trajectory. As such, + this work positions DendroPy to continue fulfilling a key supporting + role in phyloinformatics infrastructure.

+ + + Statement of Need +

DendroPy operates within a rich ecosystem of packages, frameworks, + toolkits, and software projects supporting bioinformatics and + phylogenetics research. The broader software landscape largely divides + into the following major categories,

+ + +

High-performance specialized tools for inference (e.g., + BEAST2, RAxML, + MrBayes, PAUP, etc.) + (Bouckaert, + 2014; + Ronquist + et al., 2012; + Stamatakis, + 2014; + Wilgenbusch + & Swofford, 2003);

+ + +

Python phylogenetics libraries that provide rich tree-centric + data models and operations, such as

+ + +

ETE, known in particular for powerful + phylogeny visualization capabilities + (Huerta-Cepas + et al., 2016),

+ + +

Scikit-bio and tskit + (Jai + Ram Rideout et al., 2024; + Kelleher + et al., 2018),

+ + +

TreeSwift and SuchTree, + which provide lightweight, high-performance tree + representations + (Moshiri, + 2020; + Y. + Neches & Scott, 2018), and

+ + +

hstrat and Phylotrack, + which specialize in collecting phylogenies from agent-based + evolutionary simulation + (Dolson + et al., 2024; + Moreno + et al., 2022);

+ + + + +

Python phylogenetics libraries with genome/gene-centric data + models and operations (e.g., + PyCogent/Cogent3, + BioPython, etc.) + (Cock + et al., 2009; + Knight + et al., 2007); and

+ + +

Numerous R phylogenetics packages, which are often highly + specialized but generally interoperate via + ape.phylo data structures + (Paradis + & Schliep, 2019).

+ + +

DendroPy falls largely within the second camp above. It is notable + in providing a broad portfolio of evolutionary models, but also fields + population genetics and sequence evolution utilities. DendroPy is also + notable for its comprehensive, systematic documentation and rich, + user-extensible tree representation. The library’s use cases range + across serving as a stand-alone library for phylogenetics, a component + of more complex multi-library phyloinformatics pipelines, or as an + interstitial “glue” that assembles and drives such pipelines.

+ + + Features +

Key features of DendroPy are:

+ + +

rich object-oriented representations for manipulation of + phylogenetic trees and character matrices;

+ + +

efficient, bit-level representation of nodes’ leaf + bipartitions;

+ + +

loading and saving popular phylogenetic data formats, including + NEXUS, Newick, NeXML, Phylip, and FASTA + (Felsenstein, + 1981; + Lipman + & Pearson, 1985; + Maddison + et al., 1997; + Olsen, + 1990; + Vos + et al., 2012);

+ + +

simulation of phylogenetic trees under a range of models, + including coalescent models, birth-death models, and population + genetics simulations of gene trees; and

+ + +

application scripts for performing data conversion, collating + taxon labels from multiple trees, and tree posterior distribution + summarization.

+ + +

Significant improvements have been made since DendroPy’s original + release + (Sukumaran + & Holder, 2010), including performance enhancements in + saving and loading trees, support for distance-based tree + construction, and addition of new phylogeny statistics and speciation + models.

+ + + Maintenance +

The primary focus of DenroPy’s version 5 release is to support + sustainable long-term maintenance. We have substantially reduced the + developer effort needed for ongoing releases through automation of + software tests, documentation updates, and deployment to PyPI. We hope + this will result in a regular release schedule with timely patches for + reported issues and more rapid incorporation of user + contributions.

+

The version 5 release reflects substantial investment in adopting + modern software development best practices. In version 5, DendroPy has + officially dropped support for Python 2.7, as well as Python 3.X + versions that have reached end-of-life. Focusing support on Python 3.6 + and higher simplifies cross-environment testing and allows future + development to leverage new language features. In addition, we have + established comprehensive continuous integration (CI) infrastructure + via GitHub Actions, comprising

+ + +

code linting with + Ruff;

+ + +

deploying up-to-date documentation via GitHub + pages;1

+ + +

unit tests, largely organized within the + unittest framework;

+ + +

new smoke tests using + pytest;

+ + +

code coverage reporting via the Codecov service; and

+ + +

automatic deployment of tagged versions to PyPI.

+ + +

Other behind-the-scenes activity in preparing this release includes + repair of library components flagged by the new tooling, triage of + user bug reports, applying issue tags to manage open tracker items, + establishing a code of conduct, and creating issue templates to + increase the quality of future bug reports and feature requests. + Altogether, these improvements serve as a foundation for future work + maintaining and extending DendroPy in a manner that is reliable, + stable, and responsive to user needs.

+ + + Impact +

Over its nearly 15-year history, DendroPy’s versatility and + stability have driven adoption as a core dependency of many + phylogenetics pipelines and bioinformatics software libraries. + Currently, + 85 + projects on PyPI list DendroPy as a direct dependency. + Notable projects using DendroPy include:

+ + +

PASTA, which performs multiple sequence alignment + (Mirarab + et al., 2014);

+ + +

Physcraper, which automates curation of gene trees + (Sánchez-Reyes + et al., 2021);

+ + +

Propinquity, the supertree pipeline + (Redelings + & Holder, 2017) of the Open Tree of Life project;

+ + +

DELINEATE, software for analyses discerning true speciation + from population lineages + (Sukumaran + et al., 2021);

+ + +

Archipelago, which models spatially explicit biographical + phylogenesis + (Sukumaran + et al., 2015);

+ + +

Espalier, a utility for constructing maximum agreement forests + (Rasmussen + & Guo, 2023); and

+ + +

MetaPhlAn, which extracts information about microbial community + composition from metagenomic shotgun sequencing data + (Blanco-Míguez + et al., 2023).

+ + +

During this time, DendroPy has also directly helped enable numerous + end-user phylogenetics projects. Notable examples include work on the + early natural history of birds + (Jarvis + et al., 2014), the molecular evolution of the Zika virus + (Faye + et al., 2014), and early human migration within the Americas + (García-Ortiz + et al., 2021). As of May 2024, Google Scholar counts 1,654 + works referencing DendroPy + (Sukumaran + & Holder, 2010).

+ + + Acknowledgements +

Thank you to University of Michigan Undergraduate Research + Opportunity Program participant Connor Yang for his contributions in + increasing test coverage, and to our open-source community for bug + reports, feature suggestions, and patch contributions over the years. + This research is based upon work supported by:

+ + +

the Eric and Wendy Schmidt AI in Science Postdoctoral + Fellowship, a Schmidt Sciences program (author MAM);

+ + +

the National Science Foundation grant NSF-DEB 1937725 + “COLLABORATIVE RESEARCH: Phylogenomics, spatial phylogenetics and + conservation prioritization in trapdoor spiders (and kin) of the + California Floristic Province” (author JS); and

+ + +

the National Science Foundation grant NSF-DEB 1457776 + “Collaborative Research Developing novel methods for estimating + coevolutionary processes using tapeworms and their shark and ray + hosts” (author MH).

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Documentation is hosted at + https://jeetsukumaran.github.io/DendroPy.

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