Motivation: 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.
Availability and implementation: DecentTree is open source and freely available at https://github.com/iqtree/decenttree. All code and data used in this analysis are available on Github (https://github.com/asdcid/Comparison-of-neighbour-joining-software).
© The Author(s) 2023. Published by Oxford University Press.