The Integrative Genomics Viewer (IGV) for Cancer Research

项目摘要/摘要 在新的和新兴的数据获取技术的推动下，综合基因组研究正在带来革命性的变化 我们处理癌症研究的方式和绘制新治疗方案的道路。他们需要 高通量生成和分析多种且通常是复杂类型的基因组数据。要解决这个问题 挑战，并与最终用户积极协作，我们开发并于2008年发布了广泛适用的 整合基因组学浏览器(IGV)。IGV是一个交互的、高性能的、用户友好的工具，推出了数百万 世界各地的研究人员和临床医生一年的次数。该项目的目标是确保IGV继续 跟踪和应对基因组学技术的进步和不断变化的用户需求，并保持其高水平 对癌症研究界的实用价值。我们将通过三个具体目标来实现这一目标。 目的1.进化免疫球蛋白以跟上癌症基因组学社区的需求。我们将继续 发展免疫球蛋白以利用基因组学技术和方法的最新和未来进展，这些技术和方法是移动的关键 癌症研究和治疗的前沿。我们将添加新的可视化和功能，以更好地支持 解释和验证来自短读和长读数据的复杂变体。通过与 其他项目，我们将增加新的能力，以更好地评估和解释单核苷酸和结构变体。 为了应对免疫球蛋白在审查患者肿瘤变异中的更多使用，我们将加强对这项任务的支持。 目标2.维护IGV以确保持续的高水平的实用性、可用性和可靠性。我们将继续 提供频繁的软件版本，以满足IGV的功能请求、错误报告和其他建议 用户和开发人员的社区。根据社区的意见，我们将审查IGV用户界面以 提高可用性。我们将应对不断发展的计算和技术带来的挑战和机遇 软件技术环境。我们将继续维护代码库和可下载的安装程序，并 更新它们以适应新版本的Java、Java、外部库、浏览器和操作系统。 目标3.支持IGV用户和开源开发人员社区。我们将继续提供更高的 支持级别，包括对帮助请求的快速响应；有关软件使用的深入文档；短视频 指导用户完成实用价值较高的任务；培训材料和练习。对于我们充满活力的、开源的 为IGV代码库做出贡献并在他们自己的应用程序或资源中使用IGV的开发人员社区， 支持包括：集成和扩展IGV的文档和代码示例；关于新的 通过我们的GitHub论坛进行发展；迅速审查贡献；承认他们的工作。 我们有丰富的软件工程经验，开发和分发IGV和其他软件工具 全世界数十万生物医学研究人员和临床医生使用。IGV的成功，用户驱动 开发方法、协作传统和灵活的体系结构使我们能够很好地实现 旨在进一步转变数据可视化，加快生物医学发现的步伐。

Project Summary/Abstract Driven by new and emerging technologies for data acquisition, integrative genomic studies are revolutionizing the way we approach the study of cancer and charting the way to novel treatment regimens. They require the high-throughput generation and analysis of multiple and often complex types of genomic data. To address this challenge, and in active collaboration with end users, we developed, and released in 2008, a broadly applicable Integrative Genomics Viewer (IGV). IGV is an interactive, high-performance, user-friendly tool launched millions of times a year by investigators and clinicians worldwide. The goal of this project is to ensure that IGV continues to track and respond to advances in genomics technology and changing user needs, and maintains its high level of utility for the cancer research community. We will accomplish this through our three specific aims. Aim 1. Evolve IGV to keep pace with the needs of the cancer genomics community. We will continue to evolve IGV to leverage recent and future advances in genomics technologies and methods that are key to moving cancer research and treatment forward. We will add new visualizations and features to better enable interpretation and validation of complex variants from both short and long read data. Through collaborations with other projects we will add new capabilities to better assess and interpret single nucleotide and structural variants. Responding to IGV’s increased use for review of variants in patient tumors, we will enhance support for this task. Aim 2. Maintain IGV to ensure continued high levels of utility, usability, and reliability. We will continue to provide frequent software releases to address feature requests, bug reports, and other suggestions from IGV’s community of both users and developers. Based on community input, we will review the IGV user interface to improve usability. We will address the challenges and opportunities presented by the evolving computing and software technology environment. We will continue to maintain the code base and downloadable installers and update them for new releases of Java, JavaScript, external libraries, browsers, and operating systems. Aim 3. Support the IGV user and open-source developer communities. We will continue to provide a high level of support including rapid responses to help requests; in-depth documentation on software use; short videos to walk users through tasks with high utility; training materials and exercises. For our vibrant, open-source developer community that contributes to the IGV code base and uses IGV in their own applications or resources, support includes: documentation and code examples for integrating and extending IGV; guidance on new development through our GitHub forums; prompt review of contributions; and acknowledgement of their work. We have extensive software engineering experience, developing and distributing IGV and other software tools used by hundreds of thousands of biomedical researchers and clinicians worldwide. IGV’s success, user-driven development approach, collaborative tradition, and flexible architecture make us well poised to accomplish our aims to further transform data visualization and accelerate the pace of biomedical discovery.