Xia Yujie, Li Xiaojie, Chen Xinlin, Lu Changjin, Yu Xiaoyi
Department of Ophthalmology, The First Affiliated Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China.
Guangzhou University of Chinese Medicine, Guangzhou, China.
Front Mol Biosci. 2022 Feb 11;9:843150. doi: 10.3389/fmolb.2022.843150. eCollection 2022.
Retinal Degeneration (RD) is an inherited retinal disease characterized by degeneration of rods and cones photoreceptor cells and degeneration of retinal pigment epithelial cells. The age of onset and disease progression of RD are related to genes and environment. At present, research has discovered five genes closely related to RD. They are RHO, PDE6B, MERTK, RLBP1, RPGR, and researchers have developed corresponding gene therapy methods. Gene therapy uses vectors to transfer therapeutic genes, genetically modify target cells, and correct or replace disease-causing RD genes. Therefore, identifying the pathogenic genes of RD will play an important role in the development of treatment methods for the disease. However, the traditional methods of identifying RD-related genes are mostly based on animal experiments, and currently only a small number of RD-related genes have been identified. With the increase of biological data, Xgboost is purposed in this article to identify RP-related genes. Xgboost adds a regular term to control the complexity of the model, hence using Xgboost to find out true RD-related genes from complex and massive genes is suitable. The problem of overfitting can be avoided to some extent. To verify the power of Xgboost to identify RD-related genes, we did 10-cross validation and compared with three traditional methods: Random Forest, Back Propagation network, Support Vector Machine. The accuracy of Xgboost is 99.13% and AUC is much higher than other three methods. Therefore, this article can provide technical support for efficient identification of RD-related genes and help researchers have a deeper the understanding of the genetic characteristics of RD.
视网膜变性（RD）是一种遗传性视网膜疾病，其特征是视杆和视锥光感受器细胞变性以及视网膜色素上皮细胞变性。RD的发病年龄和疾病进展与基因和环境有关。目前，研究已发现五个与RD密切相关的基因。它们是RHO、PDE6B、MERTK、RLBP1、RPGR，并且研究人员已经开发出了相应的基因治疗方法。基因治疗使用载体转移治疗性基因，对靶细胞进行基因改造，并纠正或替换导致RD的致病基因。因此，鉴定RD的致病基因将在该疾病治疗方法的开发中发挥重要作用。然而，鉴定与RD相关基因的传统方法大多基于动物实验，目前仅鉴定出少数与RD相关的基因。随着生物数据的增加，本文旨在使用Xgboost来鉴定与RP相关的基因。Xgboost添加了一个正则项来控制模型的复杂度，因此使用Xgboost从复杂且大量的基因中找出真正与RD相关的基因是合适的。可以在一定程度上避免过拟合问题。为了验证Xgboost鉴定与RD相关基因的能力，我们进行了10折交叉验证，并与三种传统方法进行比较：随机森林、反向传播网络、支持向量机。Xgboost的准确率为99.13%，AUC远高于其他三种方法。因此，本文可为高效鉴定与RD相关的基因提供技术支持，并帮助研究人员更深入地了解RD的遗传特征。
