CanvasDB: a local database infrastructure for analysis of targeted- and whole genome re-sequencing projects
CanvasDB: a local database infrastructure for analysis of targeted- and whole genome re-sequencing projects
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DOI：
10.1093/database/bau098
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发表时间：
2014-10-03
影响因子：
5.8
通讯作者：
Gyllensten, Ulf
中科院分区：
文献类型：
--
作者：
Ameur, Adam;Bunikis, Ignas;Gyllensten, Ulf
CanvasDB是一个用于管理和分析大规模并行测序（MPS）项目中遗传变异的基础设施。该系统将SNP和indel调用存储在本地数据库中，旨在处理非常大的数据集，以便使用R中的简单命令进行快速分析。系统中包含功能注释，使其适合于在人类外显子组（WES）或全基因组测序（WGS）项目中直接鉴定致病突变。该系统具有内置的过滤功能，可同时考虑所有单个样本的变异识别。这使得能够对样本组之间的变异分布进行高级比较分析，包括通过测序检测家族结构内的候选致病突变和全基因组关联。在大多数情况下，这些分析仅在几秒钟内执行，即使数据库中有数百个样本和数百万个变体。我们通过将来自1000个基因组计划中所有1092个个体的个体变异调用导入到系统中，总共超过44亿个SNP和indel，证明了canvasDB的可扩展性。我们的研究结果表明，canvasDB可以在本地服务器上对大型WGS项目进行高级分析。
CanvasDB is an infrastructure for management and analysis of genetic variants from massively parallel sequencing (MPS) projects. The system stores SNP and indel calls in a local database, designed to handle very large datasets, to allow for rapid analysis using simple commands in R. Functional annotations are included in the system, making it suitable for direct identification of disease-causing mutations in human exome-(WES) or whole-genome sequencing (WGS) projects. The system has a built-in filtering function implemented to simultaneously take into account variant calls from all individual samples. This enables advanced comparative analysis of variant distribution between groups of samples, including detection of candidate causative mutations within family structures and genome-wide association by sequencing. In most cases, these analyses are executed within just a matter of seconds, even when there are several hundreds of samples and millions of variants in the database. We demonstrate the scalability of canvasDB by importing the individual variant calls from all 1092 individuals present in the 1000 Genomes Project into the system, over 4.4 billion SNPs and indels in total. Our results show that canvasDB makes it possible to perform advanced analyses of large-scale WGS projects on a local server.