Enhance UCSC Xena Browser to Visualize Single Cell Cancer Moonshot data

摘要 新的变革性单细胞基因组学技术和空间多重原位方法提供了一种新的方法， 有机会以前所未有的分辨率询问动态肿瘤生态系统的复杂性。我们 该项目旨在使单细胞基因组学数据，如癌症登月计划， 更广泛的癌症研究社区可以探索和解释。我们建议加强UCSC Xena， 一个广泛使用的癌症基因组学数据可视化资源，具有新的全功能单细胞数据 可视化，用于制造商指定的，与Moonshot对齐的用例。我们将采用以用户为中心的设计 (UCD)，这是一个研究支持的过程和方法，涉及与用户的迭代交互， 合作者，在这些可视化的发展。我们将与两个巨蟹座密切合作 Moonshot项目，遵循UCD方法，以确保我们的可视化和界面服务于研究 需要和易于使用。在目标1中，我们将与两个癌症研究小组合作， 单细胞癌症登月数据的可视化。我们将与UCSF领导的NCI耐药性研究中心合作， 和灵敏度网络，以增强Xena浏览器，以阐明肿瘤和周围环境的变化 响应治疗的微环境，包括可视化以利用来自批量的临床结果 肿瘤数据。我们将与OHSU人类肿瘤图谱网络（HTAN）中心合作，开发多模式 HTAN数据的可视化，包括空间分辨的新交叉映射可视化， 非空间数据多模态数据。目标2将开发支持这些所需的软件基础设施 可访问的高性能单单元数据可视化。这将包括性能增强， Xena浏览器，加强了我们与RStudio的集成，并将连接器添加到单个 细胞数据分析工具，最后，结合UCSC开发的细胞状态和微环境 签名库到我们的可视化中。目标3将开发用户培训和支持，以促进采用 新的可视化和相关分析，将这些新的可视化和分析传播到最广泛的 可能的社区

ABSTRACT New transformative single-cell genomics technologies and spatial multiplex in situ methods provide an opportunity to interrogate the complexity of the dynamic tumor ecosystem at unprecedented resolution. Our project aims to make single cell genomics data, such as that from the Cancer Moonshot Initiative, more explorable and interpretable by the broader cancer research community. We propose to enhance UCSC Xena, a widely-used cancer genomics data visualization resource, with new, full-featured single cell data visualizations for investigator-specified, Moonshot-aligned use cases. We will employ User Centered Design (UCD), a research-backed process and methodology that involves iterative interactions with users and collaborators, throughout the development of these visualizations. We will work closely with two Cancer Moonshot projects, following UCD methodologies, to ensure our visualizations and interfaces serve research needs and are easy to use. In Aim 1 we will collaborate with two cancer research groups to develop novel visualizations for single cell Cancer Moonshot data. We will collaborate with UCSF-led NCI’s Drug Resistance and Sensitivity Network to enhance the Xena Browser to elucidate changes in tumors and surrounding microenvironment in response to therapy, including a visualization to leverage clinical outcomes from bulk tumor data. We will collaborate with OHSU Human Tumor Atlas Network (HTAN) center to develop multi-modal visualizations for the HTAN data, including a novel cross-mapping visualization for spatially resolved and non-spatial data multi-modal data. Aim 2 will develop the software infrastructure needed to support these accessible, high-performance single-cell data visualizations. This will include performance enhancements for the Xena Browser, hardening our integration with Jupyter Notebook/RStudio and adding connectors to single cell data analysis tools, and, finally, incorporating a UCSC-developed Cell State and Microenvironment signature library into our visualizations. Aim 3 will develop user training and support to promote adoption of new visualizations and connected analyses, disseminating these new visualizations and analyses to the widest possible community.