Cerebro: interactive visualization of scRNA-seq data
Cerebro: interactive visualization of scRNA-seq data
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DOI：
10.1093/bioinformatics/btz877
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发表时间：
2020-04-01
期刊：
影响因子：
5.8
通讯作者：
Luzi, Lucilla
中科院分区：
文献类型：
--
作者：
Hillje, Roman;Pelicci, Pier Giuseppe;Luzi, Lucilla
尽管用于分析单细胞RNA-SEQ数据的复杂生物信息学方法越来越多，但几乎没有工具可以让没有广泛生物信息学专业知识的生物学家直接显示他们自己的数据和结果并与之互动。在这里，我们介绍了Cerebro(细胞报告浏览器)，这是一个闪亮的和基于电子的独立桌面应用程序，适用于MacOS和Windows，它允许调查和检查预处理的单细胞转录数据，而不需要用户的生物信息体验。通过交互和直观的图形界面，用户可以(I)在二维或三维投影(如t-SNE或UMAP)中探索样本和细胞团之间的相似性和异质性，(Ii)显示单个基因或感兴趣的基因组的表达水平，(Iii)浏览每个样本和簇的表达最多的基因和标记基因的表，以及(Iv)显示用Monocle 2计算的轨迹。我们提供了三个从公开可用的数据集准备的例子来展示如何使用Cerebro，以及它的功能是什么。通过专注于灵活性和直接获取数据和结果，我们认为Cerebro为生物信息学家和实验生物学家提供了一个协作框架，促进有效互动，缩短数据分析和解释之间的差距。
Despite the growing availability of sophisticated bioinformatic methods for the analysis of single-cell RNA-seq data, few tools exist that allow biologists without extensive bioinformatic expertise to directly visualize and interact with their own data and results. Here, we present Cerebro (cell report browser), a Shiny- and Electron-based standalone desktop application for macOS and Windows which allows investigation and inspection of pre-processed single-cell transcriptomics data without requiring bioinformatic experience of the user. Through an interactive and intuitive graphical interface, users can (i) explore similarities and heterogeneity between samples and cell clusters in two-dimensional or three-dimensional projections such as t-SNE or UMAP, (ii) display the expression level of single genes or gene sets of interest, (iii) browse tables of most expressed genes and marker genes for each sample and cluster and (iv) display trajectories calculated with Monocle 2. We provide three examples prepared from publicly available datasets to show how Cerebro can be used and which are its capabilities. Through a focus on flexibility and direct access to data and results, we think Cerebro offers a collaborative framework for bioinformaticians and experimental biologists that facilitates effective interaction to shorten the gap between analysis and interpretation of the data.