Association Analysis Software for Mining Clinical Next-Gen Sequencing Data

用于挖掘临床下一代测序数据的关联分析软件

• 批准号: 8703156
• 负责人: TIMOTHY J DURFEE
• 金额: $ 47.8万
• 依托单位: DNASTAR, INC.
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-25 至 2015-06-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8703156
• 关键词: Automatic Data Processing; Back; Bioinformatics; Cataloging; Catalogs; Cereals; Clinical; Clinical Medicine; Clinical Research; Collaborations; Communities; Computer software; Computers; DNA Sequence; Data; Data Set; Databases; Detection; Development; Diagnosis; Diagnostics Research; Disease; Documentation; Ensure; Evaluation; Foundations; Generations; Genes; Genetic; Genome; Goals; Hour; Housing; Human Genome; Individual; Laboratories; Life; Maps; Marketing; Medical; Medical Research; Metadata; Mining; Modification; Performance; Phase; Physicians; Population; Price; Process; Prostate Cancer Vaccine; Reporting; Research Infrastructure; Research Personnel; Running; Sample Size; Sampling; Scientist; Sequence Analysis; Solid; Solutions; Suggestion; Technology; Testing; Treatment Efficacy; Vaccines; Variant; base; clinically relevant; cohort; cost effectiveness; exome; exome sequencing; feeding; flexibility; genome wide association study; genome-wide; human disease; insight; meetings; member; next generation; next generation sequencing; oncology; programs; rare variant; response; software development; tool

DESCRIPTION (provided by applicant): Remarkable improvements in throughput, accuracy and cost-effectiveness of next-generation sequencing (next-gen) technologies are ushering in a new era of clinical medicine. Genome wide association studies (GWAS) in particular have begun to leverage these advances to determine the complete catalog of common and rare variants for each member of a cohort. The resolving power of this approach has the potential to greatly accelerate our understanding, diagnosis and treatment of human disease. Unfortunately, analysis of these massive data sets requires that several disparate pieces of software be cobbled together including a large capacity next-gen sequencing assembler, variation detection modules, mapping and comparison tools for tens to hundreds of variant reports, statistical analysis packages, reporting tools, and so on. Combining and using these tools typically requires extensive bioinformatic expertise as the software is rarely well documented or supported and often depends on having elaborate hardware. These hurdles makes next-gen based GWAS inaccessible to the vast majority of the crucial user base, the physician researchers. The goal of this proposal is to assemble the essential next-gen based GWAS software components into a single coherent pipeline that that is fully equipped to meet the needs of the medical research community. Consistent with DNASTAR's 28 year tradition, the software will be easy to use, run on a reasonably priced (<$3000) desktop computer, and will be fully documented and supported. The pipeline will consist of two modules already available through DNASTAR, SeqMan NGen 3.0 (SM NGen 3.0) and ArrayStar. SM NGen 3.0, our recently released human genome scale assembly and analysis package, forms the front end of pipeline. Reference-guided assemblies of whole human genome or exome next-gen data sets produce variation reports including impact on gene features and associations with the dbSNP database. Putative variations can be verified by direct inspection of the alignment through the SeqMan Pro component of the package. Variation reports from each member of a GWAS cohort will then be fed into our multi-sample comparison and analysis program, ArrayStar, at the back end of the pipeline. ArrayStar has the infrastructure for multi-sample management and processing which can be easily adapted to GWAS analysis. These adaptations and their documentation are a central focus of this application. Critical to the successful development of this software is our collaboration with Dr. Douglas McNeel (Dept. of Oncology, UW-Madison). The exomes from a panel of prostate cancer vaccine recipients, including responders and non-responders, from the McNeel lab will be sequenced as input from which to build the pipeline using iterative cycles of development followed by evaluation by the McNeel group. This relationship offers an ideal opportunity to build the analysis and reporting software needed by physician researchers to form, test and validate GWAS generated hypotheses.

描述(由申请人提供)：下一代测序(Next-gen)技术在吞吐量、准确性和成本效益方面的显著改进正在引领临床医学的新纪元。尤其是全基因组关联研究(GWAS)已经开始利用这些进展来确定队列中每个成员的常见和罕见变异的完整目录。这种方法的解决能力有可能极大地加快我们对人类疾病的理解、诊断和治疗。不幸的是，对这些海量数据集的分析需要几个不同的软件拼凑在一起，包括大容量的下一代测序组装器、变异检测模块、用于数十到数百个变异报告的映射和比较工具、统计分析包、报告工具等等。组合和使用这些工具通常需要广泛的生物信息学专业知识，因为软件很少被很好地记录或支持，而且往往依赖于精心设计的硬件。医生研究人员表示，这些障碍使得绝大多数关键用户群无法接触到基于下一代的GWAs。这项提议的目标是将基于下一代的基本GWAS软件组件组装成一条完整装备的单一管道，以满足医学研究社区的需求。与DNAStar 28年的传统一致，该软件将易于使用，在价格合理(3000美元)的台式电脑上运行，并将得到全面的文档记录和支持。这条管道将由DNAStar已经提供的两个模块组成，即SeqMan ngen 3.0(SM ngen 3.0)和ArrayStar。SM ngen 3.0，我们最近发布的人类基因组规模组装和分析程序包，形成了管道的前端。整个人类基因组或外显子组下一代数据集的参考引导组装产生了变异报告，包括对基因特征的影响以及与数据库SNP数据库的关联。可以通过通过包装的SeqMan Pro组件直接检查对齐来验证可能的变化。然后，GWAS队列中每个成员的变异报告将被送入我们的多样本比较和分析程序ArrayStar，该程序位于管道的后端。ArrayStar拥有多样品管理和处理的基础设施，可以很容易地适应GWAS分析。这些修改及其文档是本应用程序的中心焦点。该软件成功开发的关键是我们与Douglas McNeel博士的合作。威斯康星大学麦迪逊分校肿瘤学系)。来自McNeel实验室的前列腺癌疫苗接受者小组(包括应答者和非应答者)的外显子将被测序，作为输入，使用迭代开发周期建立管道，然后由McNeel小组进行评估。这种关系提供了一个理想的机会来构建内科研究人员所需的分析和报告软件，以形成、测试和验证GWAS生成的假设。