DecentTree: scalable Neighbour-Joining for the genomic era

Weiwen Wang, James Barbetti, Thomas Wong, Bryan Thornlow, Russ Corbett-Detig, Yatish Turakhia, Robert Lanfear*, Bui Quang Minh*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    3 Citations (Scopus)

    Abstract

    Neighbour-Joining is one of the most widely used distance-based phylogenetic inference methods. However, current implementations do not scale well for datasets with more than 10 000 sequences. Given the increasing pace of generating new sequence data, particularly in outbreaks of emerging diseases, and the already enormous existing databases of sequence data for which Neighbour-Joining is a useful approach, new implementations of existing methods are warranted. Results: Here, we present DecentTree, which provides highly optimized and parallel implementations of Neighbour-Joining and several of its variants. DecentTree is designed as a stand-alone application and a header-only library easily integrated with other phylogenetic software (e.g. it is integral in the popular IQ-TREE software). We show that DecentTree shows similar or improved performance over existing software (BIONJ, Quicktree, FastME, and RapidNJ), especially for handling very large alignments. For example, DecentTree is up to 6-fold faster than the fastest existing Neighbour-Joining software (e.g. RapidNJ) when generating a tree of 64 000 SARS-CoV-2 genomes.

    Original languageEnglish
    Article numberbtad536
    JournalBioinformatics
    Volume39
    Issue number9
    DOIs
    Publication statusPublished - 1 Sept 2023

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