Universidad Peruana Cayetano Heredia

A molecular barcode and web-based data analysis tool to identify imported Plasmodium vivax malaria

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dc.contributor.author Trimarsanto, Hidayat
dc.contributor.author Amato, Roberto
dc.contributor.author Pearson, Richard D.
dc.contributor.author Sutanto, Edwin
dc.contributor.author Noviyanti, Rintis
dc.contributor.author Trianty, Leily
dc.contributor.author Marfurt, Jutta
dc.contributor.author Pava, Zuleima
dc.contributor.author Echeverry, Diego F.
dc.contributor.author Lopera-Mesa, Tatiana M.
dc.contributor.author Montenegro, Lidia M.
dc.contributor.author Tobon-Castano, Alberto
dc.contributor.author Grigg, Matthew J.
dc.contributor.author Barber, Bridget
dc.contributor.author William, Timothy
dc.contributor.author Anstey, Nicholas M.
dc.contributor.author Getachew, Sisay
dc.contributor.author Petros, Beyene
dc.contributor.author Aseffa, Abraham
dc.contributor.author Assefa, Ashenafi
dc.contributor.author Rahim, Awab G.
dc.contributor.author Chau, Nguyen H.
dc.contributor.author Hien, Tran T.
dc.contributor.author Alam, Mohammad S.
dc.contributor.author Khan, Wasif A.
dc.contributor.author Ley, Benedikt
dc.contributor.author Thriemer, Kamala
dc.contributor.author Wangchuck, Sonam
dc.contributor.author Hamedi, Yaghoob
dc.contributor.author Adam, Ishag
dc.contributor.author Liu, Yaobao
dc.contributor.author Gao, Qi
dc.contributor.author Sriprawat, Kanlaya
dc.contributor.author Ferreira, Marcelo U.
dc.contributor.author Laman, Moses
dc.contributor.author Barry, Alyssa
dc.contributor.author Mueller, Ivo
dc.contributor.author Lacerda, Marcus V. G.
dc.contributor.author Llanos Cuentas, Elmer Alejandro
dc.contributor.author Krudsood, Srivicha
dc.contributor.author Lon, Chanthap
dc.contributor.author Mohammed, Rezika
dc.contributor.author Yilma, Daniel
dc.contributor.author Pereira, Dhelio B
dc.contributor.author Espino, Fe E. J.
dc.contributor.author Chu, Cindy S.
dc.contributor.author Velez, Ivan D.
dc.contributor.author Namaik-Larp, Chayadol
dc.contributor.author Villegas, Maria F.
dc.contributor.author Green, Justin A.
dc.contributor.author Koh, Gavin
dc.contributor.author Rayner, Julian C.
dc.contributor.author Drury, Eleanor
dc.contributor.author Goncalves, Sonia
dc.contributor.author Simpson, Victoria
dc.contributor.author Miotto, Olivo
dc.contributor.author Miles, Alistair
dc.contributor.author White, Nicholas J.
dc.contributor.author Nosten, Francois
dc.contributor.author Kwiatkowski, Dominic P.
dc.contributor.author Price, Ric N.
dc.contributor.author Auburn, Sarah
dc.date.accessioned 2023-01-06T13:40:12Z
dc.date.available 2023-01-06T13:40:12Z
dc.date.issued 2022
dc.identifier.uri https://hdl.handle.net/20.500.12866/13006
dc.description.abstract Traditionally, patient travel history has been used to distinguish imported from autochthonous malaria cases, but the dormant liver stages of Plasmodium vivax confound this approach. Molecular tools offer an alternative method to identify, and map imported cases. Using machine learning approaches incorporating hierarchical fixation index and decision tree analyses applied to 799 P. vivax genomes from 21 countries, we identified 33-SNP, 50-SNP and 55-SNP barcodes (GEO33, GEO50 and GEO55), with high capacity to predict the infection’s country of origin. The Matthews correlation coefficient (MCC) for an existing, commonly applied 38-SNP barcode (BR38) exceeded 0.80 in 62% countries. The GEO panels outperformed BR38, with median MCCs > 0.80 in 90% countries at GEO33, and 95% at GEO50 and GEO55. An online, open-access, likelihood-based classifier framework was established to support data analysis (vivaxGEN-geo). The SNP selection and classifier methods can be readily amended for other use cases to support malaria control programs. en_US
dc.language.iso eng
dc.publisher Nature Research
dc.relation.ispartofseries Communications Biology
dc.rights info:eu-repo/semantics/restrictedAccess
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/deed.es
dc.subject Epidemiology en_US
dc.subject Genetics research en_US
dc.subject Machine learning en_US
dc.subject Malaria en_US
dc.subject Molecular medicine en_US
dc.title A molecular barcode and web-based data analysis tool to identify imported Plasmodium vivax malaria en_US
dc.type info:eu-repo/semantics/article
dc.identifier.doi https://doi.org/10.1038/s42003-022-04352-2
dc.subject.ocde https://purl.org/pe-repo/ocde/ford#3.03.08
dc.relation.issn 2399-3642


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