A visualization interface for BRAIN single cell data, integrating transcriptomics, epigenomics and spatial assays

项目摘要/摘要 Brain Initiative的组学数据档案NEMO包含所有BICCN单细胞单细胞数据，更多 在撰写本文时超过一百万个文件。然而，没有交互式可视化界面来检查这些 结果是可用的，许多研究人员不够熟练地使用计算工具(下载数据， 转换、加载、绘图)以利用NEMO中的数据。这使得通过以下方式来检验假设 非计算研究人员的工作比必要的要难得多，但来自这些领域专家和他们的输入 有关分子过程和细胞规格的知识对于数据的解释至关重要。 在这里，我建议在单细胞领域重复一下使基因组浏览器成为数据共享支柱的东西： 标准文件格式和它的可视化工具。新的格式是必需的，因为在云时代 技术和分布式归档，数据通常不再存储在本地。亚秒反应时间 来自远程存储是可视化所必需的，也是可能的，但现有的单单元文件格式不是 专为此访问模式而设计。此外，对于尼莫来说，能够将单细胞测试的所有结果保存在 一个已定义的结构使数据管理和访问变得更容易。我们将定义这样一种格式，它将 集成所有主要分析结果，并将所有现有的已处理数据转换为NEMO(不是原始读取 数据)转换为新格式。 然后，我们将通过我们的UCSC在NEMO网站上直接提供数据以供互动探索 手机浏览器，已经在不同的大学网站上运行。它已经被成千上万的人积极使用 以可视化我们在加州大学洛杉矶分校收集的数百个单一数据集，并已被 用于数百种科学出版物。我们将扩展我们的工具，为最新的 分析和分析类型，主要是ATAC、甲基化和空间转录成像数据，并集成 UCSC基因组浏览器，可查看染色体级别的视图和摘要。改进的拆分屏幕模式将 允许同时可视化空间数据和转录数据。此外，单元格浏览器将允许 用户可以在任何单元子集上运行最基本和最知名的分析算法，重点是 快速的响应时间，因此研究人员不必下载整个数据集来获得差异基因， 几个感兴趣的选定细胞集群的降维或特定子集群结果。 将这些软件功能和NEMO数据集成到一个用户友好的环境中将使 确保可以尽可能轻松地访问BICCN-ONICY数据，这将有助于加快实现 从现在和未来正在产生的丰富的大脑单细胞数据集中发现。

PROJECT SUMMARY / ABSTRACT The BRAIN Initiative’s -omics data archive NeMO contains all the BICCN single cell single cell data, more than one million files at the time of writing. However, no interactive visualization interface to inspect these results is available and many researchers are not proficient enough with computational tools (download data, convert, load, plot) to take advantage of the data in NeMO. This makes testing hypotheses by non-computational researchers a lot harder than necessary but the input from these domain experts and their knowledge about molecular processes and cell specification is crucial for the interpretation of the data. Here, I propose to repeat for the single cell field what has made genome browsers a pillar of data sharing: a standard file format and a visualization tool for it. A new format is a requirement, because in the era of cloud technology and distributed archives, data is usually not stored locally anymore. Sub-second reaction times from remote storage are necessary for visualization and possible but existing single cell file formats were not designed for this access pattern. In addition, for NeMO, being able to keep all results of a single cell assay in one defined structure makes data management and access easier. We will define such a format, it will integrate all the main analysis results and will convert all existing processed data in NeMO (not the raw read data) to the new format. We will then make the data available for interactive exploration directly on the NeMO website via our UCSC Cell Browser, which is already running on different University websites. It is actively used already by thousands of researchers every month to visualize hundreds of single datasets that we collected at UCSC and has been used for hundreds of scientific publications. We will extend our tool to provide direct support for the most recent assay and analysis types, mainly ATAC, methylation and spatial transcriptomics imaging data and integrate the UCSC Genome Browser for chromosome-level views and summaries. An improved split-screen mode will allow visualizing both spatial and transcriptomic data at the same time. In addition, the Cell Browser will allow users to run the most fundamental and well-known analysis algorithms on any subset of cells, with a focus on fast response time so that researchers do not have to download the whole dataset to get differential genes, dimensionality reduction or specific sub-clustering results of a few selected cell clusters of interest. Integrating these software features and the NeMO data into a single user-friendly environment will make sure that the BICCN -omics data can be accessed as easily as possible, which will help accelerate the path to discovery from the wealth of BRAIN single cell datasets being produced right now and in the future.