The Variant Explorer: a cloud-based data integration and visualization system for improving clinical interpretation of sequenced genetic variants.

 描述（由申请人提供）：该提案的目标是显著提高需要基因诊断的患者的临床决策的速度和准确性。下一代测序（NGS）技术已经彻底改变了诊断罕见遗传疾病的临床实践，并有可能成为许多医学学科的标准实践。唯一最棘手的挑战是，目前用于分析测序遗传变异的实践需要熟练的生物医学专业人员进行大量的手动分析;这种人类时间需求无法与NGS体积成比例。SolveBio的Variant Explorer（VE）是一种基于云的图形软件系统，可帮助解释变异或确定测序遗传变异的临床意义。VE旨在通过指导和删除手动分析步骤来缓解分析问题。技术创新在于SolveBio的专有数据基础设施和对可用性的优先考虑。SolveBio的核心技术是一个可编程和可扩展的数据管道，可以对基因组参考数据进行解析、规范化和版本化。SolveBio还优先考虑用户交互和体验，这是生物信息学工具通常缺乏的重点。该项目的长期目标是以指数级方式提高遗传变异分析的速度、准确性和效率，以便适合基于NGS分析的遗传疾病患者获得及时、具有成本效益和准确的结果。我们的第一阶段假设是，SolveBio的参考数据基础设施和面向用户的设计将系统地减少和简化变异解释中的手动分析步骤。我们的目标是算法汇集所有已知的和可能的符号为一个特定的变种，并建立和设计一个相关的文献整理和兰金系统。我们的第二阶段目标将包括将VE构建成模块化和完整的数据分析解决方案，其中变体分类器能够为每个变体分配初步的临床意义。基于NGS的诊断预计在未来5-10年内市场规模将增长10倍。SolveBio的变体资源管理器将有助于疏通分析瓶颈，并为广泛采用基于NGS的技术和实现精准医学铺平道路。

 DESCRIPTION (provided by applicant): The goal of this proposal is to dramatically improve speed and accuracy in clinical decision-making for patients requiring a genetic diagnosis. Next generation sequencing (NGS) technology has revolutionized the clinical practice of diagnosing rare genetic diseases and has the potential to become standard practice across many medical disciplines. The single most intractable challenge is that current practices for the analysis of sequenced genetic variants require an exorbitant amount of manual analysis by skilled biomedical professionals; this human time requirement is incapable of scaling with NGS volume. The proposed product, SolveBio's Variant Explorer (VE), is a cloud- based graphical software system that assists in variant interpretation, or the ascertaining of the clinical significance of sequenced genetic variant. The VE aims to alleviate the analysis problem by guiding and removing manual analysis steps. The technical innovation lies in SolveBio's proprietary data infrastructure and a prioritization on usability. SolveBio's core technology is a programmatic and scalable data pipeline that performs the parsing, normalizing, and versioning of genomic reference data. SolveBio also prioritizes user interaction and experience, a focus that is commonly lacking in bioinformatics tools. The long-term goal of this project is to exponentially improve speed, accuracy, and efficiency in genetic variant analysis so that patients suffering from genetic diseases suitable for NGS-based analyses receive timely, cost-efficient, and accurate results. Our Phase I hypothesis is that SolveBio's reference data infrastructure and user-oriented design will systematically reduce and streamline the manual analysis steps in variant interpretation. Our aims are to algorithmically bring together all known and possible notations for a specific variant and to build and design a relevant literature collation and rankin system. Our Phase II objectives will consist of building out the VE into a modular and complete data analysis solution with a variant classifier capable of assigning a preliminary clinical significance to each variant. NGS-based diagnostics are projected to grow tenfold in market size over the next 5-10 years. SolveBio's Variant Explorer will help unclog the analysis bottleneck and pave the way for widespread adoption of NGS-based technology and the realization of precision medicine.