ArticlePLoS neglected tropical diseases2025
CLASV: Rapid Lassa virus lineage assignment with random forest.
Article in PLoS neglected tropical diseases, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Lassa virus live tracking and lineage assignment: how nextstrain can enhance surveillance and public health in Africa and beyond.Emerging microbes & infections · 2026Article
- Temporal dynamics, climate associations, and surveillance performance of Lassa fever in Nigeria, 2020-2025: a national longitudinal analysis.Osong public health and research perspectives · 2026Article
- Sequence to structure insights into Lassa virus population-level biophysical properties and glycoprotein structure catalogue.Npj viruses · 2026Article
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Authors and funding
4 authors.
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Abstract
Lassa fever, caused by the Lassa virus (LASV), is a deadly disease characterized by hemorrhages. Annually, it affects approximately 300,000 people in West Africa and causes about 5,000 deaths. It currently has no approved vaccine and is categorized as a top-priority disease. Apart from its endemicity to West Africa, there have been exported cases in almost all continents, including several European countries. Distinct Lassa virus lineages circulate in specific regions, and have been reported to show varying immunological behaviors and may contribute to differing disease outcomes. It is therefore important to rapidly identify which lineage caused an outbreak or an exported case. We present CLASV, a machine learning-based lineage assignment tool built using a Random Forest classifier. CLASV processes raw nucleotide sequences and assigns them to the dominant circulating lineages (II, III, and IV/V) rapidly and accurately. CLASV is implemented in Python for ease of integration into existing workflows and is freely available for public use.
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Registered trials
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