高通量基因组学的数据管理
Data Management for High-Throughput Genomics
摘要：
今天的测序技术允许在几周内对单个基因组进行测序，其成本仅为原始人类基因组计划的一小部分。基因组学实验室每周都要处理数十TB的数据，这些数据必须自动处理并提供给科学家进行进一步分析。本文探讨了使用关系数据库系统作为高通量基因组学数据处理平台的潜力和局限性。特别是，我们感兴趣的高吞吐量序列数据的存储管理，并在利用SQL和用户定义的功能，数据库系统内的数据分析。我们概述了高通量基因组学的数据库设计，以及如何以一些非常规方式使用SQL Server数据库来构建此场景的原型，并且我们将讨论有关这种更加以数据库为中心的方法的可扩展性和性能的一些初步发现。
英文摘要：
Today's sequencing technology allows sequencing an individual genome within a few weeks for a fraction of the costs of the original Human Genome project. Genomics labs are faced with dozens of TB of data per week that have to be automatically processed and made available to scientists for further analysis. This paper explores the potential and the limitations of using relational database systems as the data processing platform for high-throughput genomics. In particular, we are interested in the storage management for high-throughput sequence data and in leveraging SQL and user-defined functions for data analysis inside a database system. We give an overview of a database design for high-throughput genomics, how we used a SQL Server database in some unconventional ways to prototype this scenario, and we will discuss some initial findings about the scalability and performance of such a more database-centric approach.
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