Analyzing Next-Generation Sequencing Data

描述（由申请人提供）：现代生物医学研究越来越多地使用下一代测序平台的基因组规模，包括罗氏454、Illumina GA2和ABI SOLiD。这些平台使单个实验室能够快速、廉价地从从头测序、重测序、ChIP-seq、mRNA-seq和等位型实验中生成大量基因组和转录组数据。尽管有这种产生大数据集的能力，但生物医学研究人员很少受过必要的计算和统计技术的培训，以理解这些数据。因此，许多研究人员必须依靠其他人——通常是很少受过生物学训练的计算科学家——来设计和实现适当的数据简化和数据挖掘技术。此外，大多数机构无法获得运行这些分析所需的计算资源。我们的具体目标是通过教授生物医学研究人员(1)在托管在亚马逊网络服务“云”上的远程UNIX服务器上运行分析，在为期两周的短期课程中帮助弥合这一差距；(2)对大型短读数据集进行映射和组装；(3)利用现有的短读数据解决特定的生物学问题；(4)设计能够解决自己研究问题的计算管道。所有具体目标都将伴随着相关技术的深入实践培训。我们的经验是，这种实践训练使参与者的基本计算能力有了实质性的提高。这个短期课程将帮助培养当前和下一代独立的生物医学研究人员基本的计算思维和程序，并教他们如何利用可扩展的互联网计算资源进行自己的研究。我们的最终目标是提高生物医学研究人员利用新型测序技术的效率和复杂性。

DESCRIPTION (provided by applicant): Modern biomedical research is increasingly making use of genome-scale from next-generation sequencing platforms, including Roche 454, Illumina GA2, and ABI SOLiD. These platforms make it possible for individual labs to quickly and cheaply generate vast amounts of genomic and transcriptomic data from de novo sequencing, resequencing, ChIP-seq, mRNA-seq, and allelotyping experiments. Despite this ability to generate large data sets, biomedical researchers are rarely trained in the computational and statistical techniques necessary to make sense of this data. Thus, many researchers must rely on others - often computational scientists with little biological training - to design and implement appropriate data reduction and data mining techniques. Moreover, most institutions do not have access to computational resources necessary to run these analyses. Our specific aims are to help bridge this gap in a short, two-week course, by teaching biomedical researchers to (1) run analyses on remote UNIX servers hosted in the Amazon Web Services "cloud"; (2) perform mapping and assembly on large short-read data sets; (3) tackle specific biological problems with existing short-read data; and (4) design computational pipelines capable of addressing their own research questions. All specific aims will be accompanied by in-depth hands-on practical training in the relevant techniques. Our experience is that this practical training leads to a substantial improvement in the basic computational sophistication of participants. This short course will help train the current and next generation of independent biomedical re- searchers in basic computational thinking and procedure, as well as teaching them how to make use of scalable Internet computing resources for their own research. Our end goal is increase the efficiency and sophistication with which biomedical researchers make use of novel sequencing technologies.