DendroPy 5: a mature Python library for phylogenetic computing
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866913513319956480 |
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| author | Moreno, Matthew Andres Holder, Mark T. Sukumaran, Jeet |
| author_facet | Moreno, Matthew Andres Holder, Mark T. Sukumaran, Jeet |
| contents | Contemporary bioinformatics has seen in profound new visibility 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. Insight from phylogenetic analysis has touched nearly every corner of biology. Examples range across natural history, population genetics and phylogeography, conservation biology, public health, medicine, in vivo and in silico experimental evolution, application-oriented evolutionary algorithms, 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. 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_14120 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | DendroPy 5: a mature Python library for phylogenetic computing Moreno, Matthew Andres Holder, Mark T. Sukumaran, Jeet Populations and Evolution Contemporary bioinformatics has seen in profound new visibility 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. Insight from phylogenetic analysis has touched nearly every corner of biology. Examples range across natural history, population genetics and phylogeography, conservation biology, public health, medicine, in vivo and in silico experimental evolution, application-oriented evolutionary algorithms, 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. 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. |
| title | DendroPy 5: a mature Python library for phylogenetic computing |
| topic | Populations and Evolution |
| url | https://arxiv.org/abs/2405.14120 |