Methods for data analysis.
The molecular epidemiology of infectious diseases uses a variety of techniques to assay the relatedness of disease-causing organisms to identify strains responsible for outbreaks or associated with particular phenotypes of interest (such as antibiotic resistance) and, it is hoped, provide insights into where and how these strains have emerged. The correct analysis of such data requires that we understand how the assayed variation accumulates. We discuss this with specific reference to three classes of methods: those based on gel electrophoresis of fragments generated by restriction enzymes or polymerase chain reaction (PCR), those based on microsatellites and other repeat elements, and raw sequence data from protein-coding genes. We also provide a simple example of how the likely origin of an apparently novel antibiotic-resistant strain may be identified and conclude with a discussion of some popular analysis packages and the more interesting prospects for the future in this rapidly developing field.
Hanage
William Paul
WP
Department of Infectious Disease Epidemiology, Imperial College London, UK.
Aanensen
David Michael
DM
D016000:Cluster Analysis; D003141:Communicable Diseases / Q000453:epidemiology* / Q000382:microbiology*; D004247:DNA / Q000235:genetics / Q000302:isolation & purification; D003627:Data Interpretation, Statistical; D005827:Genetics, Microbial / Q000379:methods / Q000706:statistics & numerical data; D006801:Humans; D017720:Molecular Epidemiology / Q000379:methods* / Q000706:statistics & numerical data*; D020641:Polymorphism, Single Nucleotide; D012091:Repetitive Sequences, Nucleic Acid; D017421:Sequence Analysis / Q000379:methods / Q000706:statistics & numerical data; D012984:Software
D004247:DNA