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.

中文翻译：

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中性区分类器使用决策理论方法应用于 DNA 阵列分析

最近提出了两类中性区分类器用于微生物群落分析应用。这些分类器允许在探针杂交结果太模糊而无法在分配“结合”或“无结合”结果时有足够信心的情况下的中性区域。在本文中，我们将中性区分类器的概念推广到任意数量的类别，并通过考虑探针杂交实验结果的第三类“部分结合”，将其应用于改进微生物群落分析的过程。我们引入了一系列使用高斯分布混合作为原始强度测量的 Box-Cox 幂变换模型的类分布。分层交叉验证分析用于评估建议的三类中性区分类器的功效。这篇文章在网上有补充材料。