Yang De-Wu, Li Xia, Xiao Xue, Yang Yue-Ying, Wang Jing
Department of Biological Engineering, Capital Medical University, Beijing 100069, China.
Yi Chuan. 2008 Sep;30(9):1157-62. doi: 10.3724/sp.j.1005.2008.01157.
Association between ion channel functional subtype and its genes expression is important for exploring function of ion channel, annotating function of an unknown subtype and probing into molecular mechanism of ion channel diseases. In this study, we began with noise reduction by standardizing original micro-array data, which consisted of human and mouse gene expression profiles, and then we employed principle component analysis (PCA) together with fuzzy C-mean clustering algorithm to analyze the pre-processed gene expression profiles. PCA is applied to rebuild the feature space of human gene in 21 dimensions as well as the feature space of mouse gene in 26 dimensions. Using this method we largely reduced computational complexity without losing much information involved in the original data. Subsequently, fuzzy C-mean clustering was used to classify the ion channel genes of human and mouse in their reduced feature space. In the end, four ion channel functional subtypes, such as potassium ion channels, calcium ion channel, chloride ion channel, and receptor-mediated ion channel were clustered in both human and mouse gene feature space. We applied two statistic ways to conduct significance test of the findings. In one way, we randomly sampled the data for each functional subtype of the ion channel genes and recorded the true positive rate. As a result, in both human and mouse gene feature spaces, genes that belong to one functional subtype were more likely to be clustered together than expected by chance. In the other way, we performed Kappa test and used the functional subtypes as gold standard. The result showed that consistency between the ion channel gene clusters and the ion channel gene subtypes was significantly high for both human and mouse. These results indicate that ion channel genes within the same functional subtype tend to be co-expressed at least at the mRNA-level.
离子通道功能亚型与其基因表达之间的关联对于探索离子通道的功能、注释未知亚型的功能以及探究离子通道疾病的分子机制具有重要意义。在本研究中，我们首先通过对由人类和小鼠基因表达谱组成的原始微阵列数据进行标准化来降噪，然后采用主成分分析（PCA）和模糊C均值聚类算法对预处理后的基因表达谱进行分析。PCA用于重建21维的人类基因特征空间以及26维的小鼠基因特征空间。使用这种方法，我们在很大程度上降低了计算复杂度，同时又没有丢失原始数据中包含的太多信息。随后，在其降维后的特征空间中，使用模糊C均值聚类对人类和小鼠的离子通道基因进行分类。最后，在人类和小鼠基因特征空间中都聚类出了四种离子通道功能亚型，如钾离子通道、钙离子通道、氯离子通道和受体介导的离子通道。我们应用两种统计方法对研究结果进行显著性检验。一种方法是，我们对离子通道基因的每个功能亚型的数据进行随机抽样，并记录真阳性率。结果显示，在人类和小鼠基因特征空间中，属于同一功能亚型的基因比随机预期的更有可能聚集在一起。另一种方法是，我们进行卡帕检验，并将功能亚型作为金标准。结果表明，人类和小鼠的离子通道基因簇与离子通道基因亚型之间的一致性都非常高。这些结果表明，同一功能亚型内的离子通道基因至少在mRNA水平上倾向于共表达。
