title: Accommodating error analysis in comparison and clustering of molecular fingerprints.
abstract: Molecular epidemiologic studies of infectious diseases rely on pathogen genotype comparisons, which usually yield patterns comprising sets of DNA fragments (DNA fingerprints). We use a highly developed genotyping system, IS6110-based restriction fragment length polymorphism analysis of Mycobacterium tuberculosis, to develop a computational method that automates comparison of large numbers of fingerprints. Because error in fragment length measurements is proportional to fragment length and is positively correlated for fragments within a lane, an align-and-count method that compensates for relative scaling of lanes reliably counts matching fragments between lanes. Results of a two-step method we developed to cluster identical fingerprints agree closely with 5 years of computer-assisted visual matching among 1,335 M. tuberculosis fingerprints. Fully documented and validated methods of automated comparison and clustering will greatly expand the scope of molecular epidemiology.
authors.affiliation: University of California, San Francisco, USA. hugh@molepi.stanford.edu
authors.forename: H
authors.initials: H
authors.lastname: Salamon
authors.forename: M R
authors.initials: MR
authors.lastname: Segal
authors.forename: A
authors.initials: A
authors.lastname: Ponce de Leon
authors.forename: P M
authors.initials: PM
authors.lastname: Small
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D016172:DNA Fingerprinting / Q000379:methods*; D005838:Genotype; D006801:Humans; D017720:Molecular Epidemiology / Q000379:methods*; D009169:Mycobacterium tuberculosis / Q000145:classification* / Q000235:genetics* / Q000302:isolation & purification; D012150:Polymorphism, Restriction Fragment Length; D014376:Tuberculosis / Q000453:epidemiology