ArticleNature methods2026
Rate variation and recurrent sequence errors in pandemic-scale phylogenetics.
Article in Nature methods, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Computational approaches for multimodal lineage tracing.Nature reviews. Genetics · 2026Review
- Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny.Nature methods · 2026Article
- Article
- Highly Recurrent Multinucleotide Mutations in SARS-CoV-2.Molecular biology and evolution · 2025Article
- SARS-CoV-2 sequencing artifacts associated with targeted PCR enrichment and read mapping.PloS one · 2025Article
- Addressing pandemic-wide systematic errors in the SARS-CoV-2 phylogeny.bioRxiv : the preprint server for biology · 2024Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
Phylogenetic analyses of genome sequences from infectious pathogens reveal essential information regarding their evolution and transmission, as seen during the coronavirus disease 2019 pandemic. Recently developed pandemic-scale phylogenetic inference methods reduce the computational demand of phylogenetic reconstruction from genomic epidemiological datasets, allowing the analysis of millions of closely related genomes. However, widespread homoplasies, due to recurrent mutations and sequence errors, cause phylogenetic uncertainty and biases. We present algorithms and models to substantially improve the computational performance and accuracy of pandemic-scale phylogenetics. In particular, we account for, and identify, mutation rate variation and recurrent sequence errors. We reconstruct a reliable and public sequence alignment and phylogenetic tree of >2 million severe acute respiratory syndrome coronavirus 2 genomes encapsulating the evolutionary history and global spread of the virus up to February 2023.
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