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Lessons learned from implementing a national infrastructure in Sweden for storage and analysis of next-generation sequencing data

机译:从在瑞典实施国家级基础设施以存储和分析下一代测序数据中学到的经验教训

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摘要

Analyzing and storing data and results from next-generation sequencing (NGS) experiments is a challenging task, hampered by ever-increasing data volumes and frequent updates of analysis methods and tools. Storage and computation have grown beyond the capacity of personal computers and there is a need for suitable e-infrastructures for processing. Here we describe UPPNEX, an implementation of such an infrastructure, tailored to the needs of data storage and analysis of NGS data in Sweden serving various labs and multiple instruments from the major sequencing technology platforms. UPPNEX comprises resources for high-performance computing, large-scale and high-availability storage, an extensive bioinformatics software suite, up-to-date reference genomes and annotations, a support function with system and application experts as well as a web portal and support ticket system. UPPNEX applications are numerous and diverse, and include whole genome-, de novo- and exome sequencing, targeted resequencing, SNP discovery, RNASeq, and methylation analysis. There are over 300 projects that utilize UPPNEX and include large undertakings such as the sequencing of the flycatcher and Norwegian spruce. We describe the strategic decisions made when investing in hardware, setting up maintenance and support, allocating resources, and illustrate major challenges such as managing data growth. We conclude with summarizing our experiences and observations with UPPNEX to date, providing insights into the successful and less successful decisions made.
机译:下一代数据测序(NGS)实验的数据和结果的分析和存储是一项艰巨的任务,因为数据量的不断增加以及分析方法和工具的频繁更新受到阻碍。存储和计算已经超出了个人计算机的能力,并且需要合适的电子基础设施来进行处理。在这里,我们将描述UPPNEX,这是一种基础结构的实现,它是根据瑞典的数据存储和NGS数据分析需求量身定制的,服务于来自主要测序技术平台的各种实验室和多种仪器。 UPPNEX包括用于高性能计算,大规模和高可用性存储的资源,广泛的生物信息学软件套件,最新的参考基因组和注释,具有系统和应用程序专家的支持功能以及网络门户和支持票务系统。 UPPNEX的应用是多种多样的,包括全基因组测序,从头测序和外显子组测序,靶向重测序,SNP发现,RNASeq和甲基化分析。有超过300个利用UPPNEX的项目,其中包括大型项目,例如捕蝇器的排序和挪威云杉的排序。我们描述了在投资硬件,设置维护和支持,分配资源时所做出的战略决策,并说明了诸如管理数据增长之类的主要挑战。最后,总结迄今为止在UPPNEX上的经验和观察,以洞悉成功和失败的决策。

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