Sun Jun, Huang Yi, Wang Xiaodong, Li Wenfu, An Dongyan, Gao Yong, Xiong Hui, Zhou Zaiwei, Xu Xiong, Deng Xuxu, Wang Xiaoqing, Huang Hui, Peng Zhiyu, Zhang Wei, Yu Shihui, Wang Liang, Gu Weihong, Huang Shangzhi, Shen Yiping
Boston Children's Hospital, Harvard Medical School, Boston, MA 02115, USA; Maternal and Child Health Hospital of Guangxi Zhuang Autonomous Region, Nanning, Guangxi 530000, China.
Zhonghua Yi Xue Yi Chuan Xue Za Zhi. 2020 Mar 10;37(3):345-351. doi: 10.3760/cma.j.issn.1003-9406.2020.03.021.
Bioinformatic analysis and variant classification are the key components of high-throughput sequencing-based genetic diagnostic approach. This consensus is part of the effort to develop a standardized process for next generation sequencing (NGS)-based test for germline mutations underlying Mendelian disorders in China. The flow-chart, common software, key parameters of bioinformatics pipeline for data processing, annotation, storage and variant classification are reviewed, which is aimed to help improving and maintaining a high-quality process and obtaining consistent outcomes for NGS-based molecular diagnosis.
生物信息学分析和变异分类是基于高通量测序的基因诊断方法的关键组成部分。本共识是在中国努力开发基于下一代测序（NGS）检测孟德尔疾病潜在种系突变的标准化流程的一部分。本文回顾了用于数据处理、注释、存储和变异分类的生物信息学流程的流程图、常用软件、关键参数，旨在帮助改进和维持高质量的流程，并为基于NGS的分子诊断获得一致的结果。
