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Abstract Detail


Au, Scarlet [1], McKenzie, Patrick [2], Eaton, Deren [3].

A new tool for measuring phylogenetic distance metrics for investigating genealogical variation.

The Python programming language is widely used in data science and bioinformatics, but still lacks many basic computational tools for phylogenomics research. distmetric is a new Python module for computing distances between phylogenetic trees using a variety of metrics. Different tree distance metrics can reveal different aspects of variation among collections of trees, such as bootstrap or posterior samples, gene tree collections, or genomic sliding windows. distmetric is fast and parallelizable. Trees are parsed and represented as toytree/ete3 TreeNode objects, and distances can be calculated pairwise, randomly (with respect to genomic distances), or relative to a consensus. Current supported metrics include Robinson-Foulds and several Quartet-based methods. The module is designed as part of toytree – a comprehensive phylogenetic tree drawing and manipulation Python library – and follows a similar minimalist and interactive framework. As a demonstration, we revisit a well-known phylogenomic dataset to explore the implications of using different distance measurements for phylogenetic applications.

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1 - Columbia University, Ecology, Evolution, and Environmental Biology, Schermerhorn Ext., 1200 Amsterdam Avenue, New York, NY, 10027, USA
2 - Columbia University, Ecology, Evolution, and Environmental Biology, 10th Floor Schermerhorn Ext., 1200 Amsterdam Ave., New York, NY, 10027, United States
3 - Columbia University, Ecology, Evolution, And Environmental Biology, 1200 Amsterdam Ave. , Schermerhorn Ext. Office 1007, New York, NY, 10027, United States

distance metrics

Presentation Type: Poster
Session: P3, Phylogenomics Posters
Location: Virtual/Virtual
Date: Wednesday, July 21st, 2021
Time: 5:00 PM(EDT)
Number: P3PL013
Abstract ID:877
Candidate for Awards:None

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