A Community Driven Framework for Genome Based Clinical Diagnostics

基于基因组的临床诊断的社区驱动框架

基本信息

批准号：
9293355
负责人：
Karen Louise Eilbeck
金额：
$ 61.26万
依托单位：
UNIVERSITY OF UTAH
依托单位国家：
美国
项目类别：
财政年份：
2015
资助国家：
美国
起止时间：
2015-09-21 至 2020-06-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9293355
关键词：
Address Adoption Algorithms American Awareness Bioinformatics Centers for Disease Control and Prevention (U.S.)Clinical Clinical Informatics Communication Communities Complex Computer software Data Data Analyses Databases Descriptor Detection Diagnostic Diagnostic tests Ensure Face Failure Feedback Future Genbank Genes Genetic screening method Genome Genomics Goals Government Graph Haplotypes Health Informatics Laboratories Medical Metadata Methods National Human Genome Research Institute Nomenclature Output Pathologist Patients Phase Positioning Attribute Process Public Health Applications Research Recommendation Records Reporting Reproducibility Research Scientist Site Software Framework Software Tools Standardization Technology Terminology Testing University Hospitals Utah Variant Work base clinical application clinical care clinical diagnostics clinical sequencing college community college data format data sharing design disorder prevention exome experience field study file format flexibility genetic variant genome sequencing genomic data improved next generation sequencing novel personalized health care portability pressure public health relevance quality assurance software development tool web site whole genome working group

项目摘要

DESCRIPTION (provided by applicant): Personal genome sequences from next generation sequencing technologies are permeating clinical care via diagnostic testing. Clinical labs are under pressure to handle this data in unambiguous, reproducible ways, and provide interpretations that are comparable across testing sites, but face many difficulties to do so. Over the last several years the 'variant file', has emerged as the common currency for exchange and analyses of personal genome sequences for research, and now clinical purposes. These files describe every position in a personal genome that differs from the reference GenBank genome sequence. Given their widespread use, the variant file is a logical starting point for designing a format suitable for clinical applications. Currently variant file styles are widely divergent, ther is not uniformity in the way that complex variants are annotated and genomics has not embraced the use of medical data standards. The diagnostic genomics community, aware of these issues, has mobilized a working group to provide recommendations and requirements to unify variant annotation, to improve public health and clinical applications. For example, without clear standards for capturing variant sequence data, sharing data for the following applications is hindered: across laboratories for quality assurance, with databases for making an interpretation, with a patient record for future use. This proposal addresses the problems with polymorphic variant description by providing novel algorithms to define sequence variants and by developing file formats and software to communicate this information, using guidance from the clinical diagnostic community. The standardized format, VCFclin, and co-developed software tools will end information loss and ambiguity as genomics data flow from sequencing machines, through variant calling and analysis pipelines to interpretation and clinical use.

描述（由应用程序提供）：下一代测序技术的个人基因组序列正在通过诊断测试渗透临床护理。临床实验室的压力是以明确的，可重复的方式处理这些数据，并提供了在测试站点之间可比的解释，但是要这样做遇到许多困难。超过在过去的几年中，“变体文件”已成为交换和分析个人基因组序列的共同货币，现在是临床目的。这些文件描述了个人基因组中与参考GenBank基因组序列不同的每个位置。鉴于它们的宽度使用，变体文件是设计适合临床应用的格式的逻辑起点。当前的变体文件样式是广泛不同的，这并不是统一性的，因为复杂的变体被注释，并且基因组学并未接受医学数据标准的使用。意识到这些问题的诊断基因组学界已经动员了一个工作组，以提供建议和要求以统一变异注释，以改善公共卫生和临床应用。例如，如果没有明确的捕获变体序列数据的标准，则妨碍了以下应用程序共享数据：跨实验室以进行质量保证，并具有进行解释的数据库，并具有未来使用的患者记录。该建议通过使用临床诊断社区的指导来定义序列变体，并开发文件格式和软件来定义序列变体，并开发文件格式和软件通过开发文件格式和软件来解决多态性变体描述的问题。标准化格式，VCFCLIN和共同开发的软件工具将以基因组数据流来结束信息丢失和歧义，从测序机，通过变体调用和分析管道到解释和临床使用。