An innovative WGS platform for discovery, annotation, and interpretation of all forms of human genetic variation.

一个创新的全基因组测序平台，用于发现、注释和解释所有形式的人类遗传变异。

• 批准号: 9928201
• 负责人: Brent Pedersen
• 金额: $ 7.45万
• 依托单位: BASE2 GENOMICS, LLC
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-05-28 至 2019-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9928201
• 关键词: Acceleration; Acute; Algorithmic Software; Automation; Automobile Driving; Biotechnology; Businesses; Catalogs; Cloud Computing; Collaborations; Computing Methodologies; DNA sequencing; Data; Data Compression; Data Set; Databases; Detection; Diagnosis; Diagnostic; Diagnostics Research; Engineering; Ensure; Environment; Ewings sarcoma; Family; Frequencies; Funding; Future; Genes; Genetic; Genetic Polymorphism; Genetic Variation; Genome; Genomics; Genotype; Grant; Growth; Health Insurance Portability and Accountability Act; Hospitals; Human Genetics; Human Genome; Individual; Informatics; Knowledge; Mendelian disorder; Modernization; Patient Data Privacy; Performance; Pharmacogenetics; Pharmacologic Substance; Population; Process; Provider; Quality Control; Rare Diseases; Recording of previous events; Research; Resources; Retinal blind spot; Sampling; Science; Secure; Security; Seeds; Short Tandem Repeat; Single Nucleotide Polymorphism; Speed; Structure; Technology; Testing; Time; Utah; Variant; Work; base; cohort; computational platform; computerized data processing; cost; data submission; data visualization; database structure; disease phenotype; exome sequencing; experimental study; genetic variant; genome analysis; genome sequencing; genomic platform; gigabyte; human disease; improved; indexing; innovation; innovative technologies; insertion/deletion mutation; parallelization; programs; sequencing platform; terabyte; web services; whole genome

PROJECT SUMMARY Modern DNA sequencing technologies have transformed our ability to interrogate human genomes in a single experiment, thereby eliminating the inherent blind spots of gene panels and whole exome sequencing. Furthermore, recent speed and economy improvements are driving the cost of whole genome sequencing (WGS) down to that of WES; therefore, we foresee a transition over the next two years to WGS as the de facto test for human disease research and diagnosis in academic labs, hospitals, and both biotechnology and pharmaceutical companies. Indeed, conservative estimates project 20 million human genomes will be sequenced in next decade. However, the transition to research and diagnostics driven by WGS presents a substantial data processing burden, as a single WGS sample represents at least 100 gigabytes and converting the raw data into a comprehensive set of genetic variation requires an intricate, rapidly changing, and computationally onerous workflow. Based on our history of developing innovative computational methods for genomic research and motivated by the acute need for advanced, scalable computing platforms, the applicant team founded Base2 Genomics (Base2). Base2 has created an innovative platform for WGS data processing, quality control, variant detection and prioritization, and data visualization using Amazon Web Services (AWS) cloud computing. Developed in close collaboration with AWS engineers, the fundamental strengths of the Base2 platform are its speed, cost, capacity for parallelization, and, most importantly, its ability to accurately identify all forms of genetic variation, whereas most other commercial offerings focus on solely the easiest forms (SNPs and INDELs) of variation to discover. We argue that, in order to maximize the research, diagnostic, and pharmacogenetics utility of WGS, it is imperative to create a complete catalog of all variation in each sequenced genome. In this proposal, we will further improve our technologies with the following aims: Aim 1. Develop proprietary technologies for prioritizing and annotating copy-number and structural variation via population-scale databases. We have developed STIX (STructural variant IndeX), a proprietary compression algorithm and database for efficiently profiling evidence for SV among thousands of human genomes. We propose to leverage this innovation to create unique, proprietary STIX databases, and an associated SV annotation engine to facilitate accurate prioritization of SV for customer WGS cohorts. Aim 2. Create a secure, high-performance customer data submission portal. We will develop a secure customer data submission portal that maximizes efficiency and security while allowing customers to upload data and invoke processing through the Base2 platform.

项目总结 现代DNA测序技术已经改变了我们在一个单一的 实验，从而消除了基因面板和整个外显子组测序的固有盲点。 此外，最近的速度和经济改进正在推动全基因组测序的成本 (WGS)下至WES；因此，我们预计在未来两年内向WGS过渡是事实上的 在学术实验室、医院和生物技术和医疗机构进行人类疾病研究和诊断测试 制药公司。事实上，保守估计2000万个人类基因组将是 在接下来的十年里被测序。然而，由WGS推动的向研究和诊断的过渡提供了一个 相当大的数据处理负担，因为单个WGS样本表示至少100 GB和转换 将原始数据转化为一套全面的遗传变异需要复杂、快速变化和 计算繁琐的工作流程。 基于我们为基因组研究开发创新计算方法的历史 在对先进、可扩展计算平台的迫切需求的推动下，申请团队成立了Base2 基因组学(基础2)。Base2打造了WGS数据处理、质量控制、变种的创新平台 使用Amazon Web服务(AWS)云计算进行检测和优先级排序以及数据可视化。 Base2平台是与AWS工程师密切合作开发的，其基本优势在于 速度、成本、并行化能力，最重要的是，它能够准确识别所有形式的 基因变异，而大多数其他商业产品只关注最简单的形式(SNPs和 Indels)的变异有待发现。我们认为，为了最大限度地提高研究、诊断和 WGS的药物遗传学效用，必须创建一个完整的目录，其中每个变异 测序的基因组。在这份提案中，我们将进一步改进我们的技术，目标如下： 目标1.开发专有技术，对副本数量和结构进行优先排序和注释 通过人口规模的数据库进行变异。我们开发了STIX(结构变量指数)，这是一种专有的 用于有效分析数千人中SV证据的压缩算法和数据库 基因组。我们建议利用这一创新来创建独特的专有STIX数据库，并 关联的SV注释引擎，便于为客户WGS队列准确确定SV的优先级。 目标2.创建安全、高性能的客户数据提交门户。我们将开发一种安全的 客户数据提交门户，最大限度地提高效率和安全性，同时允许客户上传 数据，并通过Base2平台调用处理。