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

基本信息

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
项目类别：
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

项目摘要

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.

项目概要癌症测序项目已鉴定出大量 DNA 突变，这些突变在癌症中具有重要意义尚不明白。为了更好地了解这些突变的影响，我们的团队开发了一个软件用于癌症突变计算分析的工具，可以一次分析数百万个突变。这个工具作为一个漏斗，帮助研究人员找到最有可能提供信息的少量突变来自测序项目中发现的大量突变。该软件允许用户设计组合多个突变评估指标的方法，并生成更优先的突变列表可能具有重要的生物学意义。这些评估指标包括分子结果、生物信息学识别致病突变和驱动突变的分数、人群中突变的频率、以前的肿瘤组织类型中的发生情况、文献指针以及注释的蛋白质结构和可视化网络。基于网络的管道版本 - 癌症相关变异分析工具包 (CRAVAT) 已发布广泛采用（2020 年平均每月提交 3000 多个工作岗位）。我们吸引了一个用户社区涵盖基础和临床癌症研究人员，他们的研究都依赖于高通量肿瘤测序工作。 2019年，我们推出了OpenCRAVAT，它的特点是开源代码库和开放的应用程序商店提供工具和资源，可用于更好地了解突变的重要性和影响。应用商店由用户社区驱动；根据用户请求和应用程序对新应用程序进行优先级排序商店包含许多由外部工具开发人员直接贡献的应用程序。目前应用商店聚合了来自 70 多个组织的工具，这些工具可以组合起来识别其突变分子影响有助于肿瘤发生、预后和治疗选择。初步采用我们的 OpenCRAVAT 工具令人鼓舞，前两年本地软件包下载量超过 10,000 个。我们期望鉴于 DNA 的重要性日益增加，OpenCRAVAT 将被更大的社区采用癌症研究中的测序数据。我们将继续确保我们的工具能够与其他工具互操作信息学工具和服务，可以在云计算等不同的计算环境中运行和本地安装以维护数据隐私。