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STing: accurate and ultrafast genomic profiling with exact sequence matches.
Espitia-Navarro, Hector F; Chande, Aroon T; Nagar, Shashwat D; Smith, Heather; Jordan, I King; Rishishwar, Lavanya.
Afiliación
  • Espitia-Navarro HF; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
  • Chande AT; PanAmerican Bioinformatics Institute, Cali, Valle del Cauca 760043, Colombia.
  • Nagar SD; Applied Bioinformatics Laboratory, Atlanta, GA 30332, USA.
  • Smith H; School of Biological Sciences, Georgia Institute of Technology, Atlanta, GA 30332, USA.
  • Jordan IK; PanAmerican Bioinformatics Institute, Cali, Valle del Cauca 760043, Colombia.
  • Rishishwar L; Applied Bioinformatics Laboratory, Atlanta, GA 30332, USA.
Nucleic Acids Res ; 48(14): 7681-7689, 2020 08 20.
Article en En | MEDLINE | ID: mdl-32619234
Genome-enabled approaches to molecular epidemiology have become essential to public health agencies and the microbial research community. We developed the algorithm STing to provide turn-key solutions for molecular typing and gene detection directly from next generation sequence data of microbial pathogens. Our implementation of STing uses an innovative k-mer search strategy that eliminates the computational overhead associated with the time-consuming steps of quality control, assembly, and alignment, required by more traditional methods. We compared STing to six of the most widely used programs for genome-based molecular typing and demonstrate its ease of use, accuracy, speed and efficiency. STing shows superior accuracy and performance for standard multilocus sequence typing schemes, along with larger genome-scale typing schemes, and it enables rapid automated detection of antimicrobial resistance and virulence factor genes. STing determines the sequence type of traditional 7-gene MLST with 100% accuracy in less than 10 seconds per isolate. We hope that the adoption of STing will help to democratize microbial genomics and thereby maximize its benefit for public health.
Asunto(s)

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Tipificación de Secuencias Multilocus / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Evaluation_studies Idioma: En Revista: Nucleic Acids Res Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Banco de datos: MEDLINE Asunto principal: Algoritmos / Tipificación de Secuencias Multilocus / Secuenciación de Nucleótidos de Alto Rendimiento Tipo de estudio: Evaluation_studies Idioma: En Revista: Nucleic Acids Res Año: 2020 Tipo del documento: Article País de afiliación: Estados Unidos