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

P R Hunter

doi:10.1093/bioinformatics/9.4.403

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

P R Hunter

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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.

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Bacteria Bacterial Typing Techniques Candida albicans Cluster Analysis Microbiological Techniques Monte Carlo Method Reproducibility of Results Software Journal Article

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P R Hunter. 1993. A numerical method for allocating microbial isolates to strain types when characterized by typing methods that are not 100% reproducible.. https://doi.org/10.1093/bioinformatics%2F9.4.403

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