dc.contributor.author
Daodu, Richard Olumide
dc.contributor.author
Awotoro, Ebenezer
dc.contributor.author
Ulrich, Jens-Uwe
dc.contributor.author
Kühnert, Denise
dc.date.accessioned
2025-10-17T09:23:05Z
dc.date.available
2025-10-17T09:23:05Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/49858
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-49583
dc.description.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.
en
dc.format.extent
13 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Sequence alignment
en
dc.subject
Phylogenetic analysis
en
dc.subject.ddc
600 Technik, Medizin, angewandte Wissenschaften::610 Medizin und Gesundheit::616 Krankheiten
dc.title
CLASV: Rapid Lassa virus lineage assignment with random forest
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.articlenumber
e0013512
dcterms.bibliographicCitation.doi
10.1371/journal.pntd.0013512
dcterms.bibliographicCitation.journaltitle
PLOS Neglected Tropical Diseases
dcterms.bibliographicCitation.number
9
dcterms.bibliographicCitation.volume
19
dcterms.bibliographicCitation.url
https://doi.org/10.1371/journal.pntd.0013512
refubium.affiliation
Mathematik und Informatik
refubium.affiliation.other
Institut für Mathematik

refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1935-2735
refubium.resourceType.provider
WoS-Alert