面向测序技术的外显子组拷贝数变异检测算法研究与应用

项目名称： 面向测序技术的外显子组拷贝数变异检测算法研究与应用

项目编号： No.31301092

项目类型： 青年科学基金项目

立项/批准年度： 2014

项目学科： 生物科学

项目作者： 林勇

作者单位： 上海理工大学

项目金额： 23万元

中文摘要： 拷贝数变异是一种广泛分布于人类基因组中的重要遗传变异。随着大量外显子组重测序项目的开展，现有针对外显子组测序数据的拷贝数变异检测算法少且存在读信息利用不足、精度不高的问题。本项目拟设计一个基于隐马尔科夫模型的外显子组拷贝数变异检测算法，针对外显子组测序数据特点的设计并整合读数据中的多种信息来提高检测精度。同时在设计的算法基础上开发具有数据可视化、参数优化设定功能的软件，为研究人员的实际使用提供便利。作为一个实际应用，本研究将新检测软件应用于骨质疏松症和银屑病外显子组测序数据的拷贝数变异检测，并通过关联分析定位疾病的潜在基因。本研究不仅为外显子组的拷贝数变异的检测提供有力的支持，而且能通过检测得到的变异进行关联分析，为研究疾病的遗传机制提供帮助。

中文关键词： 拷贝数变异；外显子组；变异检测；测序技术；关联分析

英文摘要： Copy number variant is an important genetic variation widely distributed in the human genome. With the large number of exome re-sequencing projects carrying out, there are few copy number variant algorithms specifically for exome sequencing read data. The problems of not high enough detection performances and underutilization of the read information exist in these algorithms. This research intends to design a hidden Markov model-based detection algorithm for exome sequencing data. Design for the exome sequencing data characteristics and integration of a variety of information in the read data will help to improve the detection accuracy. We will also develop a software based on our detection algorithm with data visualization and parameter optimal setting function to facilitate the actual use for the researchers. As a practical application, we will use the new detection software to detect copy number variation of osteoporosis and psoriasis exome sequencing data, and locate potential disease gene by association analyses. This study provide strong support for the exome copy number variant detection, also give an assistance to study the genetic mechanisms of disease by the detected variants association analysis.

英文关键词： Copy Number Variant；Exome；Variants Detection；Sequencing Technology；Association Analyses