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A brief primer on genomic epidemiology: lessons learned from Mycobacterium tuberculosis
Author(s) -
Guthrie Jennifer L.,
Gardy Jennifer L.
Publication year - 2017
Publication title -
annals of the new york academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.712
H-Index - 248
eISSN - 1749-6632
pISSN - 0077-8923
DOI - 10.1111/nyas.13273
Subject(s) - genomics , mycobacterium tuberculosis , transmission (telecommunications) , tuberculosis , epidemiology , biology , molecular epidemiology , computational biology , genetic epidemiology , data science , genetics , medicine , genome , computer science , genotype , gene , pathology , telecommunications
Genomics is now firmly established as a technique for the investigation and reconstruction of communicable disease outbreaks, with many genomic epidemiology studies focusing on revealing transmission routes of Mycobacterium tuberculosis . In this primer, we introduce the basic techniques underlying transmission inference from genomic data, using illustrative examples from M. tuberculosis and other pathogens routinely sequenced by public health agencies. We describe the laboratory and epidemiological scenarios under which genomics may or may not be used, provide an introduction to sequencing technologies and bioinformatics approaches to identifying transmission‐informative variation and resistance‐associated mutations, and discuss how variation must be considered in the light of available clinical and epidemiological information to infer transmission.