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 有机会以前所未有的分辨率探索动态的肿瘤生态系统的复杂性。我们的 该项目旨在使单细胞基因组学数据，如来自癌症登月倡议的数据， 更广泛的癌症研究社区可以探索和解释。我们建议增强UCSC Xena， 一个广泛使用的癌症基因组数据可视化资源，具有新的、功能齐全的单细胞数据 针对调查员指定的、与Moonshot一致的用例的可视化。我们将采用以用户为中心的设计 (UCD)，这是一种研究支持的过程和方法，涉及与用户和 合作者，在这些可视化的整个开发过程中。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，并且易于使用。在目标1中，我们将与两个癌症研究小组合作开发新的 单细胞癌登月数据的可视化。我们将与加州大学旧金山分校领导的NCI抗药性合作 和敏感度网络来增强Xena浏览器，以阐明肿瘤及其周围的变化 微环境对治疗的响应，包括利用批量临床结果的可视化 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数据可视化，包括一种新的空间分辨率和 非空间数据多模式数据。AIM 2将开发支持这些功能所需的软件基础设施 可访问的高性能单元格数据可视化。这将包括以下方面的性能增强 Xena浏览器，加强了我们与Jupyter Notebook/RStudio的集成，并将连接器添加到 细胞数据分析工具，最后，结合UCSC开发的细胞状态和微环境 将签名库添加到我们的可视化中。AIM 3将开发用户培训和支持，以促进采用 新的可视化和关联分析，将这些新的可视化和分析最广泛地传播到 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.