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: 8727829
• 负责人: TIMOTHY J DURFEE
• 金额: $ 15万
• 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/8727829
• 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; 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（下一代）技术的吞吐量，准确性和成本效益的显着改善正在迎来临床医学的新时代。尤其是基因组广泛的关联研究（GWAS）已开始利用这些进步来确定同类人群每个成员的共同和稀有变体的完整目录。这种方法的解决能力有可能极大地加速我们对人类疾病的理解，诊断和治疗。不幸的是，对这些大规模数据集的分析要求将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程序，变化检测模块，映射和比较工具，用于数十个变体报告，统计分析包，统计分析包，报告工具等。将这些工具结合起来并使用这些工具通常需要广泛的生物信息学专业知识，因为该软件很少有文献记载或支持，并且通常取决于具有精心制作的硬件。这些障碍使下一代GWAS对绝大多数关键的用户群，医师研究人员无法访问。 该提案的目的是将基于下一代GWAS的基本GWAS软件组件组装成一个连贯的管道，该管道完全有能力满足医学研究界的需求。与DNASTAR的28年传统一致，该软件将易于使用，在价格合理（<$ 3000）的台式计算机上运行，​​并将得到充分记录和支持。该管道将​​由已通过DNASTAR，SEQMAN NGEN 3.0（SM NGEN 3.0）和ARRAYSTAR提供的两个模块组成。我们最近发布的人类基因组量表组装和分析软件包SM NGEN 3.0构成了管道的前端。整个人类基因组或外显组下一代数据集的参考引导组件产生了变化报告，包括对基因特征的影响以及与DBSNP数据库的关联。可以通过包装的Seqman Pro组件直接检查对齐方式来验证推定的变化。然后，来自GWAS队列的每个成员的变异报告将被送入管道后端的多样本比较和分析程序Arraystar。 ArrayStar具有用于多样本管理和处理的基础架构，可以很容易地适用于GWAS分析。这些改编及其文档是本应用程序的核心重点。 对于成功开发该软件至关重要的是我们与Douglas McNeel博士（UW-Madison肿瘤学系）的合作。麦克尼尔实验室（McNeel Lab）的一组前列腺癌疫苗接受者（包括响应者和非反应者）的外部将被序列作为输入，以使用迭代的开发周期来构建管道，然后由McNeel Group进行评估。这种关系提供了一个理想的机会，可以建立医生研究人员所需的分析和报告软件，以形成，测试和验证GWAS产生的假设。