ACCOMMODATING ERROR ANALYSIS IN COMPARISON AND CLUSTERING OF MOLECULAR FINGERPRINTS

Molecular epidemiologic studies of infectious diseases rely on pathoge n genotype comparisons, which usually yield patterns comprising sets o f DNA fragments (DNA fingerprints). We use a highly developed genotypi ng system, IS6110-based restriction fragment length polymorphism analy sis of Mycobacterium tuberculosis, to develop a computational method t hat automates comparison of targe numbers of fingerprints. Because err or 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 ye ars of computer-assisted visual matching among 1,335 M. tuberculosis f ingerprints. Fully documented and validated methods of automated compa rison and clustering will greatly expand the scope of molecular epidem iology.