Software Systems for Detecting Rare Muations

用于检测罕见突变的软件系统

• 批准号: 7745833
• 负责人: TODD M SMITH
• 金额: $ 11万
• 依托单位: GEOSPIZA, INC.
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2010-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7745833
• 关键词: Address; Algorithms; Americas; Basic Science; Bioconductor; Biological Assay; Biology; Cancer Diagnostics; Cataloging; Catalogs; Cause of Death; Cells; Clinic; Clinical; Communities; Community Developments; Complex; Complex Mixtures; Computer software; DNA; DNA Sequence; Data; Data Set; Detection; Development; Diagnostic; Diagnostic tests; Disease; Drug resistance; Environment; Error Sources; Experimental Designs; Future; Genetic; Genetic Variation; Genome; Goals; Health; Heart Diseases; Human; Individual; Laboratories; Leadership; Life; Link; Malignant Neoplasms; Maps; Measures; Medicine; Methods; Morphologic artifacts; Mutation; Mutation Detection; Noise; Online Systems; Output; Pharmacotherapy; Phase; Phenotype; Play; Population; Positioning Attribute; Preparation; Probability; Procedures; Process; Reading; Relative (related person); Research; Research Personnel; Research Project Grants; Resources; Role; Sampling; Sampling Biases; Sampling Studies; Scientist; Sensitivity and Specificity; Sequence Alignment; Small Business Innovation Research Grant; Software Tools; Somatic Mutation; Source; System; Techniques; Technology; Testing; Time; Variant; Vision; War; Work; anticancer research; base; cancer cell; cancer type; clinical application; computerized tools; cost; data management; design; effective therapy; improved; insight; instrument; neoplastic cell; new technology; next generation; novel; open source; pancreatic neoplasm; prognostic; prognostic indicator; public health relevance; research study; response; single molecule; software development; software systems; statistics; tool; trend; tumor; tumor growth; web based interface

DESCRIPTION (provided by applicant): In November 2008, The Scientist opened an on-line opinion piece with the following quote: "After tens of billions of US federal dollars (plus billions more from private sources) and nearly 40 years of aggressive research, the war on cancer is depressingly far from over. Cancer will soon become the leading cause of death in America, passing heart disease. At some point in their lives, 43% of the public will get some form of cancer." While much progress has been made over the years, effective treatments for many forms of cancer are still lacking. Until the many forms of cancer are better understood, treatment options will continue to lag behind. Next generation DNA sequencing (NGS) technologies hold great promise as tools for building a new understanding of cancer and its origins. Deep sequencing provides more sensitive ways to detect the germline and somatic mutations that cause different types of cancer as well as identify new mutations within small subpopulations of tumor cells that can be prognostic indicators of tumor growth or drug resistance. The ultimate goal is to use NGS technologies in the clinic. Before this vision can be realized, many obstacles must be overcome. Assay costs must be significantly lowered and sample throughput must be substantially increased relative to today's capabilities. Achieving this goal will require that we have streamlined procedures for sample preparation and laboratory processes, a complete understanding of NGS systems, error profiles, and assay dynamics, and robust validatable software systems to support diagnostic tests in the clinical enterprise. Geospiza's FinchLab software platform addresses a large number of issues related to operating NGS instruments and laboratory processes in clinical environments. However, our understanding of NGS errors and how to completely characterize NGS datasets, with respect to their potential to deliver high quality information, is incomplete. Through the proposed research, Geospiza and collaborators at the Mayo Clinic will remove many of the obstacles that keep this vision of cancer diagnostics from becoming reality. In the Phase I project, we will test the feasibility of developing clinical systems by characterizing a limited number of NGS datasets for true variants, false positive, and false negative errors by cataloging discrepant bases relative to control sequences, with respect to sequence contexts, random noise, laboratory steps, and instrument artifacts. The catalogs will then be used to develop statistical algorithms that can analyze large numbers of aligned reads and assign variant detection probabilities to individual bases, as well as calculate summary statistics that can be used to assign descriptive values to datasets from individual samples, and subsequently identify sample artifacts and issues related to sample processing. Geospiza will combine the insights gained, and new software tools developed, into the FinchLab system to give researchers better ways to work with NGS data and more clear-cut methods for visualizing genetic assay results presented in web-based interfaces. In addition, Geospiza will promote community involvement by making many of the core algorithms available through BioConductor. PUBLIC HEALTH RELEVANCE: The SBIR project "Software Systems for Detecting Rare Mutations" will deliver new software technologies to further advance the applications for deep DNA sequencing in personalized medicine by improving methods for detecting rare mutations that define cancer types and determine how a cancer cell may grow and respond to, or resist, treatment. In addition to improving cancer research and diagnostics, the software developed will have general use for any application where DNA sequencing is used to understand the genetic basis of human health, disease, and response to drug therapies.

描述（由申请人提供）：2008年11月，这位科学家在线观点上发表了以下报价：“经过数以万计的美国联邦美元（加上数十亿美元的私人来源）和近40年的积极研究，对癌症的战争远离超越了癌症。尽管多年来取得了很多进展，但仍缺乏对许多形式的癌症的有效治疗方法。在更好地理解许多形式的癌症之前，治疗方案将继续落后。下一代DNA测序（NGS）技术具有巨大的希望，是建立对癌症及其起源的新理解的工具。深层测序提供了更敏感的方法来检测引起不同类型癌症的种系和体细胞突变，并在肿瘤细胞的小亚群中鉴定新突变，这些突变可能是肿瘤生长或耐药性的预后指标。最终目标是在诊所使用NGS技术。在实现这一愿景之前，必须克服许多障碍。必须大大降低测定成本，相对于当今的功能，样品吞吐量必须大大增加。实现此目标将要求我们简化了用于样本准备和实验室过程的程序，对NGS​​系统的完整了解，错误配置文件和测定动力学以及可靠的有效软件系统，以支持临床企业中的诊断测试。 Geospiza的Finchlab软件平台解决了与临床环境中运营的NGS仪器和实验室过程有关的大量问题。但是，我们对NGS错误的理解以及如何完全表征NGS数据集在提供高质量信息的潜力方面是不完整的。通过拟议的研究，Mayo诊所的Geospiza和合作者将消除许多使癌症诊断愿景成为现实的障碍。在I阶段项目中，我们将通过表征有限数量的NGS数据集来测试开发临床系统的可行性，用于真实变体，假阳性和假负错误，通过相对于序列上下文，随机噪声，实验室，实验室步骤和仪器措施来分类差异基础相对于控制序列。然后，这些目录将用于开发统计算法，这些算法可以分析大量对齐的读取并将变体检测概率分配给单个基础，并计算可用于从单个样本中为数据集分配描述值的摘要统计信息，并随后确定与样品处理相关的样本和问题。 Geospiza将将获得的见解和开发的新软件工具结合到Finchlab系统中，以使研究人员更好地使用NGS数据和更清晰的方法，以可视化基于Web的界面中介绍的基因测定结果。此外，Geospiza将通过生物导体提供许多核心算法来促进社区参与。 公共卫生相关性：SBIR项目“用于检测稀有突变的软件系统”将提供新的软件技术，以进一步推动个性化医学中深层DNA测序的应用，通过改进检测稀有的方法来检测稀有的突变，这些突变定义癌症类型并确定癌细胞可能如何成长和对抗反应或抗药性。除了改善癌症的研究和诊断外，开发的软件还将用于任何应用DNA测序来理解人类健康，疾病和对药物疗法反应的遗传基础的应用。