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Rapid low-cost whole-genome sequencing (WGS) is revolutionizing microbiology; however, complementary advances in accessible, reproducible, and rapid analysis techniques are required to realize the potential of these data. Here, investigations of the genus Neisseria illustrated the gene-by-gene conceptual approach to the organization and analysis of WGS data. Using the gene and its link to phenotype as a starting point, the BIGSdb database, which powers the PubMLST databases, enables the assembly of large open-access collections of annotated genomes that provide insight into the evolution of the Neisseria, the epidemiology of meningococcal and gonococcal disease, and mechanisms of Neisseria pathogenicity.

Original publication

DOI

10.1128/JCM.00301-16

Type

Journal article

Journal

J Clin Microbiol

Publication Date

08/2016

Volume

54

Pages

1949 - 1955

Keywords

Computational Biology, Genomics, Gonorrhea, High-Throughput Nucleotide Sequencing, Humans, Meningococcal Infections, Neisseria