Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet

作者：Salamon John; Qian Xiaoyan; Nilsson Mats; Lynn David John^*

来源：Cell Systems, 2018, 6(5): 626-+.

DOI：10.1016/j.cels.2018.03.010

In situ sequencing methods generate spatially resolved RNA localization and expression data at an almost single-cell resolution. Few methods, however, currently exist to analyze and visualize the complex data that is produced, which can encode the localization and expression of a million or more individual transcripts in a tissue section. Here, we present InsituNet, an application that converts in situ sequencing data into interactive network-based visualizations, where each unique transcript is a node in the network and edges represent the spatial co-expression relationships between transcripts. InsituNet is available as an app for the Cytoscape platform at http://apps.cytoscape.org/apps/insitunet. InsituNet enables the analysis of the relationships that exist between these transcripts and can uncover how spatial co-expression profiles change in different regions of the tissue or across different tissue sections.

• 出版日期2018-5-23