Yu Hua, Jeske Daniel R, Ruegger Paul, Borneman James
Amgen, Inc., One Amgen Center Drive, Thousand Oaks, CA 91320-1799, USA.
J Agric Biol Environ Stat. 2010 Dec;15(4):474-490. doi: 10.1007/s13253-010-0034-6.
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.
最近提出了两类中性区分类器用于微生物群落分析应用。对于探针杂交结果过于模糊以至于无法对“结合”或“未结合”结果有足够信心的情况，这些分类器允许一个中性区域。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过程。我们引入了一类类分布，它使用高斯分布的混合作为原始强度测量的Box-Cox幂变换的模型。分层交叉验证分析用于评估所提出的三类中性区分类器的功效。本文有在线补充材料。
