Gene expression classification using epigenetic features and DNA sequence composition in the human embryonic stem cell line H1
Gene expression classification using epigenetic features and DNA sequence composition in the human embryonic stem cell line H1
复制标题
使用人胚胎干细胞系 H1 中的表观遗传特征和 DNA 序列组成进行基因表达分类
作者：
Su Wen-Xia;Li Qian-Zhong;Zhang Lu-Qiang;Fan Guo-Liang;Wu Cheng-Yan;Yan Zhen-He;Zuo Yong-Chun;Li QZ
在现有的研究中，表观遗传因素与基因表达相关。然而，目前还缺乏基于表观遗传因素对高表达和低表达基因进行准确分类的定量模型。本研究以人类胚胎干细胞系(H1)为研究对象，将组蛋白修饰、DNA甲基化、DNA可及性、转录因子和三核苷酸组成与支持向量机相结合，提出了一种新的机器学习方法。结果表明，当考虑表观遗传特征时，预测精度将显著提高。对于10次交叉验证检验，最优模型的预测准确率和Matthews相关系数分别高达95.96%和0.92；对于独立数据集检验，最优模型的预测准确率和Matthews相关系数分别高达95.58%和0.92。该模型为在缺乏基因表达数据的情况下，利用遗传和表观遗传学数据判断基因是高表达还是低表达提供了一种很好的方法。我们的分析方法的网络服务器GECES是在http://202.207.14.87:8032/fuwu/GECES/index.asp，上建立的，这样其他科学家就可以通过我们的网络服务器轻松地获得他们想要的结果，而不需要通过数学细节。
Epigenetic factors are known to correlate with gene expression in the existing studies. However, quantitative models that accurately classify the highly and lowly expressed genes based on epigenetic factors are currently lacking. In this study, a new machine learning method combines histone modifications, DNA methylation, DNA accessibility, transcription factors, and trinucleotide composition with support vector machines (SVM) is developed in the context of human embryonic stem cell line (H1). The results indicate that the predictive accuracy will be markedly improved when the epigenetic features are considered. The predictive accuracy and Matthews correlation coefficient of the best model are as high as 95.96% and 0.92 for 10-fold cross-validation test, and 95.58% and 0.92 for independent dataset test, respectively. Our model provides a good way to judge a gene is either highly or lowly expressed gene by using genetic and epigenetic data, when the expression data of the gene is lacking. And a web-server GECES for our analysis method is established at http://202.207.14.87:8032/fuwu/GECES/index.asp, so that other scientists can easily get their desired results by our web-server, without going through the mathematical details.