SPRING: a kinetic interface for visualizing high dimensional single-cell expression data
SPRING: a kinetic interface for visualizing high dimensional single-cell expression data
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DOI：
10.1093/bioinformatics/btx792
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发表时间：
2018-04-01
期刊：
影响因子：
5.8
通讯作者：
Klein, Allon M.
中科院分区：
文献类型：
--
作者：
Weinreb, Caleb;Wolock, Samuel;Klein, Allon M.
动机：单细胞基因表达谱技术可以绘制组织或生物体中的细胞状态。随着这些技术变得越来越普遍，需要计算工具来探索它们产生的数据。特别是，可视化连续的基因表达拓扑结构可以得到改善，因为目前的工具往往片段基因表达continua或捕捉复杂的人口topology.Results的功能有限：力导向布局的k-最近邻图可以可视化连续的基因表达拓扑结构的方式，保持高维关系，并捕捉复杂的人口拓扑结构。我们描述了SPRING，一个使用力导向布局的数据过滤，规范化和可视化的管道，并表明当应用于造血祖细胞和上气道上皮细胞的分支基因表达轨迹时，它揭示了比现有方法更详细的生物学关系。SPRING的可视化也比随机可视化方法（如tSNE，一种最先进的工具）更具可重复性。我们提供SPRING作为一个交互式的Web工具，具有易于使用的GUI。
Motivation: Single-cell gene expression profiling technologies can map the cell states in a tissue or organism. As these technologies become more common, there is a need for computational tools to explore the data they produce. In particular, visualizing continuous gene expression topologies can be improved, since current tools tend to fragment gene expression continua or capture only limited features of complex population topologies.Results: Force-directed layouts of k-nearest-neighbor graphs can visualize continuous gene expression topologies in a manner that preserves high-dimensional relationships and captures complex population topologies. We describe SPRING, a pipeline for data filtering, normalization and visualization using force-directed layouts and show that it reveals more detailed biological relationships than existing approaches when applied to branching gene expression trajectories from hematopoietic progenitor cells and cells of the upper airway epithelium. Visualizations from SPRING are also more reproducible than those of stochastic visualization methods such as tSNE, a state-of-the-art tool. We provide SPRING as an interactive web-tool with an easy to use GUI.