Por favor, use este identificador para citar o enlazar a este item:
http://hdl.handle.net/10261/171310
COMPARTIR / EXPORTAR:
SHARE CORE BASE | |
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | |
Título: | Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase |
Autor: | Ezewudo, Matthew; Borens, Amanda; Chiner-Oms, Álvaro CSIC ORCID ; Miotto, Paolo; Chindelevitch, Leonid; Starks, Angela M.; Hanna, Debra; Liwski, Richard; Zignol, Matteo; Gilpin, Christopher; Niemann, Stefan; Kohl, Thomas Andreas; Warren, Robin M.; Crook, Derrick; Gagneux, Sebastien; Hoffner, Sven; Rodrigues, Camilla; Comas, Iñaki CSIC ORCID ; Engelthaler, David M; Alland, David; Rigouts, Leen; Lange, Christoph; Dheda, Keertan; Hasan, Rumina; McNerney, Ruth; Cirillo, Daniela M.; Schito, Marco; Rodwell, Timothy C; Posey, James | Fecha de publicación: | 18-oct-2018 | Editor: | Springer Nature | Citación: | Scientific Reports 8(1):15382 (2018) | Resumen: | Drug-resistant tuberculosis poses a persistent public health threat. The ReSeqTB platform is a collaborative, curated knowledgebase, designed to standardize and aggregate global Mycobacterium tuberculosis complex (MTBC) variant data from whole genome sequencing (WGS) with phenotypic drug susceptibility testing (DST) and clinical data. We developed a unified analysis variant pipeline (UVP) ( https://github.com/CPTR-ReSeqTB/UVP ) to identify variants and assign lineage from MTBC sequence data. Stringent thresholds and quality control measures were incorporated in this open source tool. The pipeline was validated using a well-characterized dataset of 90 diverse MTBC isolates with conventional DST and DNA Sanger sequencing data. The UVP exhibited 98.9% agreement with the variants identified using Sanger sequencing and was 100% concordant with conventional methods of assigning lineage. We analyzed 4636 publicly available MTBC isolates in the ReSeqTB platform representing all seven major MTBC lineages. The variants detected have an above 94% accuracy of predicting drug based on the accompanying DST results in the platform. The aggregation of variants over time in the platform will establish confidence-graded mutations statistically associated with phenotypic drug resistance. These tools serve as critical reference standards for future molecular diagnostic assay developers, researchers, public health agencies and clinicians working towards the control of drug-resistant tuberculosis. | Descripción: | 10 Pages, 1 Figure, 3 Tables. Supplementary information: http://dx.doi.org/10.1038/s41598-018-33731-1 | Versión del editor: | http://dx.doi.org/10.1038/s41598-018-33731-1 | URI: | http://hdl.handle.net/10261/171310 | DOI: | 10.1038/s41598-018-33731-1 | E-ISSN: | 2045-2322 |
Aparece en las colecciones: | (IBV) Artículos |
Ficheros en este ítem:
Fichero | Descripción | Tamaño | Formato | |
---|---|---|---|---|
2018 Sci Rep 8-15382.pdf | 1,4 MB | Adobe PDF | Visualizar/Abrir |
CORE Recommender
PubMed Central
Citations
43
checked on 18-mar-2024
SCOPUSTM
Citations
52
checked on 14-mar-2024
WEB OF SCIENCETM
Citations
53
checked on 23-feb-2024
Page view(s)
304
checked on 17-mar-2024
Download(s)
184
checked on 17-mar-2024
Google ScholarTM
Check
Altmetric
Altmetric
Artículos relacionados:
NOTA: Los ítems de Digital.CSIC están protegidos por copyright, con todos los derechos reservados, a menos que se indique lo contrario.