OpenCRAVAT: Informatics Tools for High-Throughput Analysis of Cancer Mutations

OpenCRAVAT：用于癌症突变高通量分析的信息学工具

• 批准号: 10617371
• 负责人: Rachel Karchin
• 金额: $ 65.31万
• 依托单位: JOHNS HOPKINS UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-05-15 至 2027-04-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10617371
• 关键词: Address; Adopted; Adoption; Architecture; Bioinformatics; Cancer Patient; Characteristics; Clinical; Cloud Computing; Cloud Service; Collaborations; Collection; Communities; Complex; Computer Analysis; Computer software; Custom; DNA Sequence; DNA Sequence Alteration; DNA sequencing; Data; Data Commons; Data Set; Databases; Disease; Educational workshop; Ensure; Environment; Epitopes; Evaluation; Feedback; Frequencies; Friends; Gene Frequency; Genes; Genomics; Growth; Haplotypes; Human; Individual; Investments; Language; Literature; Malignant Neoplasms; Measures; Molecular; Mutation; Occupations; Online Systems; Pathogenicity; Population; Prognosis; Property; Recurrence; Research Personnel; Resources; Running; Sampling; Selection for Treatments; Services; Side; Software Tools; Source; Source Code; Subgroup; System; Techniques; Time; Training; Tumor Tissue; Untranslated RNA; Update; Variant; Visualization; Visualization software; Work; anticancer research; base; cancer genomics; cancer subtypes; cloud platform; cohort; computerized tools; data privacy; design; driver mutation; flexibility; genetic variant; genomics cloud; graphical user interface; hackathon; high throughput analysis; improved; in silico; informatics tool; interoperability; meetings; open source; outreach; parallel processing; patient subsets; protein structure; recruit; skills; social media; success; symposium; task analysis; tool; tumor; tumorigenesis; usability; web server; web-based tool

PROJECT SUMMARY Cancer sequencing projects have identified a very large number of DNA mutations whose importance in cancer is not yet understood. To better understand the impact of these mutations, our team has produced a software tool for computational analysis of cancer mutations that can analyze millions of mutations at one time. This tool works as a funnel to help researchers to find the small number of mutations that are most likely to be informative from the very large number of mutations discovered in a sequencing project. The software allows users to design ways to combine multiple mutation evaluation metrics, and generate a prioritized list of mutations that are more likely to be biologically important. These evaluation metrics include the molecular consequence, bioinformatic scores to identify pathogenic and driver mutations, frequency of the mutation in human populations, previous occurrence in tumor tissue types, pointers to literature, and visualization of annotated protein structures and networks. A web-based version of the pipeline - Cancer Related Analysis of Variants Toolkit (CRAVAT) has been widely adopted (3000+ jobs submitted/month on average in 2020). We have attracted a user community that spans both basic and clinical cancer researchers, all of whom rely on high-throughput tumor sequencing in their work. In 2019, we introduced OpenCRAVAT, which is distinguished by an open source codebase and an open app store of tools and resources that can be used to better understand the importance and impact of mutations. The app store is driven by the user community; new apps are prioritized based upon user requests and the app store includes many apps that were contributed directly by outside tool developers. The app store currently aggregates tools from over 70 organizations, and these tools can be combined to identify mutations whose molecular impact contributes to tumorigenesis, prognosis and treatment selection. Initial adoption of our OpenCRAVAT tool is encouraging, with over 10,000 local package downloads in the first two years. We expect that OpenCRAVAT will be adopted by a much larger community, given the increasing importance of DNA sequencing data in cancer research. We will continue to ensure that our tools are interoperable with other informatics tools and services, and can be run in different computational environments such as cloud computing and local installation to maintain data privacy.

项目摘要 癌症测序项目已经确定了大量的DNA突变，其在癌症中的重要性 还没有被理解。为了更好地了解这些突变的影响，我们的团队制作了一个软件， 癌症突变的计算分析工具，可以一次分析数百万个突变。此工具 作为一个漏斗，帮助研究人员找到最有可能提供信息的少量突变， 从测序项目中发现的大量突变中。该软件允许用户设计 联合收割机组合多个突变评估度量的方法，并生成一个优先级更高的突变列表， 可能具有重要的生物学意义这些评价指标包括分子结果、生物信息学 用于识别致病性和驱动突变的评分，人群中突变的频率， 肿瘤组织类型中的发生率、文献指针以及注释蛋白质结构的可视化， 网络.一个基于网络的管道版本-癌症相关变异分析工具包（CRAVAT）已被 广泛采用（2020年平均每月提交3000多个职位）。我们吸引了一个用户社区， 跨越基础和临床癌症研究人员，他们都依赖于高通量肿瘤测序， 工作在2019年，我们推出了OpenCRAVAT，它以开源代码库和开放的 应用程序商店的工具和资源，可用于更好地了解突变的重要性和影响。 应用程序商店由用户社区驱动;新应用程序根据用户请求和应用程序优先级排序 商店包括许多由外部工具开发人员直接贡献的应用程序。App Store目前 汇集了来自70多个组织的工具，这些工具可以组合起来识别 分子影响有助于肿瘤发生、预后和治疗选择。初步通过我们的 OpenCRAVAT工具令人鼓舞，在头两年有超过10，000个本地软件包下载。我们预计 OpenCRAVAT将被更大的社区采用，因为DNA的重要性越来越大。 癌症研究中的测序数据。我们将继续确保我们的工具与其他工具的互操作性。 信息学工具和服务，并可以在不同的计算环境中运行，如云计算 和本地安装以维护数据隐私。