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Neutral Zone Classifiers Using a Decision-Theoretic Approach With Application to DNA Array Analyses

Abstract

Two-class neutral zone classifiers were recently proposed for use in microbial community profiling applications. These classifiers allow a region of neutrality for cases where probe hybridization outcomes are too ambiguous to have adequate confidence in assigning a “binding” or “no binding” result. In this paper, we generalize the idea of neutral zone classifiers to an arbitrary number of classes and apply it to improve the process of microbial community profiling by considering a third class for the outcome of probe hybridization experiments, “partial binding.” We introduce a family of class distributions that uses a mixture of Gaussian distributions as a model for a Box–Cox power transformation of the raw intensity measurements. Stratified cross-validation analyses are used to assess the efficacy of the proposed three-class neutral zone classifier. This article has supplementary material online.

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