ArticleVirus evolution2024
SARS-CoV-2 lineage assignments using phylogenetic placement/UShER are superior to pangoLEARN machine-learning method.
Article in Virus evolution, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Compressive pangenomics using mutation-annotated networks.Nature genetics · 2026Article
- SARS-CoV-2 variants: biology, pathogenicity, immunity and control.Nature reviews. Microbiology · 2026Review
- Article
- CLASV: Rapid Lassa virus lineage assignment with random forest.PLoS neglected tropical diseases · 2025Article
- Real-time, multi-pathogen wastewater genomic surveillance with Freyja 2.medRxiv : the preprint server for health sciences · 2025Article
- Genetic diversity of H9N2 avian influenza viruses in poultry across China and implications for zoonotic transmission.Nature microbiology · 2025Article
- Short-Read and Long-Read Whole Genome Sequencing for SARS-CoV-2 Variants Identification.Viruses · 2025Article
- Applying prospective tree-temporal scan statistics to genomic surveillance data to detect emerging SARS-CoV-2 variants and salmonellosis clusters in New York City.International journal of epidemiology · 2025Article
- Review
- F1ALA: ultrafast and memory-efficient ancestral lineage annotation applied to the huge SARS-CoV-2 phylogeny.Virus evolution · 2024Article
- SCORPIO: a utility for defining and classifying mutation constellations of virus genomes.Bioinformatics (Oxford, England) · 2023Article
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Authors and funding
14 authors.
Funding
Abstract
With the rapid spread and evolution of SARS-CoV-2, the ability to monitor its transmission and distinguish among viral lineages is critical for pandemic response efforts. The most commonly used software for the lineage assignment of newly isolated SARS-CoV-2 genomes is pangolin, which offers two methods of assignment, pangoLEARN and pUShER. PangoLEARN rapidly assigns lineages using a machine-learning algorithm, while pUShER performs a phylogenetic placement to identify the lineage corresponding to a newly sequenced genome. In a preliminary study, we observed that pangoLEARN (decision tree model), while substantially faster than pUShER, offered less consistency across different versions of pangolin v3. Here, we expand upon this analysis to include v3 and v4 of pangolin, which moved the default algorithm for lineage assignment from pangoLEARN in v3 to pUShER in v4, and perform a thorough analysis confirming that pUShER is not only more stable across versions but also more accurate. Our findings suggest that future lineage assignment algorithms for various pathogens should consider the value of phylogenetic placement.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.