We propose the hierarchical Projective Adaptive Resonance Theory (PART) algorithm for classification of gene expression data. This algorithm is realized by combing transposed quasi-supervised PART and unsupervised PART. We develop the corresponding validation statistics for each process and compare it with other clustering algorithms in a case study of tuberculosis (TB). First, we use sample-based transposed quasi-supervised PART to obtain optimal clustering results of samples distinguished by time post-infection and the representative genes for each cluster including up-regulated, down-regulated and stable genes. The up- and down-regulated genes show more than 90% similarity to the result derived from Linear Models for Microarray Data and are verified by weighted k-nearest neighbor model on TB projection. Second, we use gene-based unsupervised PART algorithm to cluster these representative genes where functional enrichment analysis is conducted in each cluster. We further confirm the main immune response of human macrophage-like THP-1 cells against TB within 2 days is type I interferon-mediated innate immunity. This study demonstrates how hierarchical PART algorithm analyzes microarray data. The sample-based quasi-supervised PART extracts representative genes and narrows down the shortlist of disease-relevant genes and gene-based unsupervised PART classifies representative genes that help to interpret immune response against TB.

中文翻译：

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使用分层投影自适应共振理论从微阵列数据中聚类基因：结核病的案例研究

我们提出了用于基因表达数据分类的层次投影自适应共振理论（PART）算法。该算法是通过组合转置的准监督PART和无监督PART来实现的。我们为每个过程开发相应的验证统计数据，并将其与结核病 (TB) 案例研究中的其他聚类算法进行比较。首先，我们使用基于样本的转置准监督 PART 来获得按感染后时间和每个集群的代表基因（包括上调、下调和稳定基因）区分的样本的最佳聚类结果。上调和下调基因与微阵列数据线性模型得出的结果具有 90% 以上的相似性，并通过 TB 投影上的加权 k 最近邻模型进行验证。第二，我们使用基于基因的无监督 PART 算法对这些代表性基因进行聚类，并在每个聚类中进行功能富集分析。我们进一步证实了人类巨噬细胞样THP-1细胞在2天内对结核病的主要免疫反应是I型干扰素介导的先天免疫。本研究展示了分层 PART 算法如何分析微阵列数据。基于样本的准监督 PART 提取代表性基因并缩小疾病相关基因的候选名单，基于基因的非监督 PART 对有助于解释针对 TB 的免疫反应的代表性基因进行分类。我们进一步证实了人类巨噬细胞样THP-1细胞在2天内对结核病的主要免疫反应是I型干扰素介导的先天免疫。本研究展示了分层 PART 算法如何分析微阵列数据。基于样本的准监督 PART 提取代表性基因并缩小疾病相关基因的候选名单，基于基因的非监督 PART 对有助于解释针对 TB 的免疫反应的代表性基因进行分类。我们进一步证实了人类巨噬细胞样THP-1细胞在2天内对结核病的主要免疫反应是I型干扰素介导的先天免疫。本研究展示了分层 PART 算法如何分析微阵列数据。基于样本的准监督 PART 提取代表性基因并缩小疾病相关基因的候选名单，基于基因的非监督 PART 对有助于解释针对 TB 的免疫反应的代表性基因进行分类。