面向精准医学的基因突变数据分类与融合研究

目的：通过调研现有的基因突变数据标准，包括分类标准、命名标准以及组织标准，制定一套整合式的基因突变数据分类体系以融合多来源异构的突变数据。方法：从ClinVar和COSMIC突变数据库中获取基因突变数据，根据数据特征对基因突变数据进行标准化融合。通过与已制定的分类体系进行映射，对融合后的基因突变数据进行标准化分类注释。结果：构建的基因突变分类体系包括术语34条，突变数据库包括突变概念746 504个，突变术语1 083 397个。结论：基因突变数据分类体系可提供一种有效的基因突变数据分类和突变数据整合方案，对推动突变数据的融合、标准化与共享和疾病的精准治疗具有重要意义。

Classification of gene mutation data and gene fusion for precision medicine

Objective To develop an integrated classification system for gene mutation data in order to fuse the isomeric gene mutation data in multi-resources by investigating the existing standards for gene mutation data, including classification standards, nomenclature standards and organization standards. Methods The gene mutation data were extracted from the ClinVar and COSMIC mutation databases and fused with standard methods according to their characteristics. The fused gene mutation data were classified with annotations by mapping the developed classification system. Results The classification system for gene mutation data was consisted of 34 terminologies and the gene mutation database was consisted of 746 504 concepts and 1 083 397 mutation terminologies. Conclusion The classification system for gene mutation data can provide an effective plan for the classification and integration of gene mutation data, and is of great importance for promoting the fusion, standardization and sharing of gene mutation data, and the precision treatment of diseases.