This is SPRTA: assessing phylogenetic confidence at pandemic scales
De Maio, N.; Ly-Trong, N.; Minh, B. Q.; Goldman, N.
Show abstract
Phylogenetics plays a central role in evolutionary biology and genomic epidemiology. Assessing phylogenetic confidence and reliability is therefore crucial and methods to do this, such as Felsensteins bootstrap, are among the most used in modern science. However, methods based on Felsensteins bootstrap suffer from excessive computational demand, and are unsuitable for large datasets. Furthermore, most of these methods emerge from a cladistic framework which makes their results hard to interpret in the context of genomic epidemiology. We propose SPRTA (" SPR-based Tree Assessment"), an efficient and interpretable approach to assess confidence in phylogenetic trees. SPRTA shifts the paradigm of phylogenetic support measurement from evaluating the confidence in clades (groupings of taxa) to genome evolution histories, for example assessing if a lineage evolved from another considered lineage or not. This focus on evolutionary histories is particularly valuable in genomic epidemiology, where typically the evolutionary and transmission history of a pathogen are of interest, not clade content. We illustrate the use of SPRTA by investigating a global SARS-CoV-2 phylogenetic tree relating > 2M genomes, highlighting plausible alternative evolutionary origins of many SARS-CoV-2 variants. We have implemented SPRTA within the free and open source maximum likelihood phylogenetic software MAPLE, available from https://github.com/NicolaDM/MAPLE.
Matching journals
The top 5 journals account for 50% of the predicted probability mass.
Similar papers in this journal
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.