Genotypes of infectious organisms are becoming the foundation for
epidemiologic studies of infectious disease. Central to the use of such data is
a means for comparing genotypes. We develop methods for this purpose in the
context of DN fingerprint genotyping of tuberculosis, but our approach is
applicable to many fingerprintbased genotyping systems and/or
organisms. Data available on replicate (laboratory) strains here reveal that
(i) error in fingerprint band size is proportional to band size and (ii) errors
are positively correlated within a fingerprint. Comparison (or matching) scores
computed to account for this error structure need to be
“standardized” in order to properly rank the comparisons. We
demonstrate the utility of using extreme value distributions to effect such
standardization. Several estimation issues for the extreme value parameters are
discussed, including a lack of robustness of (approximate) maximum likelihood
estimates. Interesting findings to emerge from examination of quantiles of
standardized matching scores include (i) formal significance is not attainable
when querying a database for a given fingerprint pattern and (ii) maximal
matching probabilities are not necessarily monotonely decreasing with
increasing numbers of fingerprint bands.
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