A numerical method for allocating microbial isolates to strain types when characterized by typing methods that are not 100% reproducible

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Abstract

Many methods for typing microbial strains are not 100% reproducible. This can create problems when deciding whether different groups of isolates are really distinct or represent typing errors or variation of a single strain. Neither hierarchical clustering nor iterative partitioning methods are suited for analysing such data. A novel iterative partitioning method is described which allows for the uncertainty of the typing method in use. Before grouping strains, the maximum dimension of the groups is set based on a previous knowledge of the typing method's reproducibility. Isolates are only allocated to a group if they differ from that group's typical strain type by less than the number of reaction differences required to distinguish between two strains. In a series of Monte Carlo studies the accuracy of strain allocation was found to be very good, even when the two groups were situated close to each other.
Original languageEnglish
Pages (from-to)403-405
JournalBioinformatics
Volume9
Issue number4
DOIs
Publication statusPublished - Aug 1993

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