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

Salamon J, Qian X, Nilsson M, Lynn DJ

Cell Systems 6 (5) 626-630.e3 [2018-05-23; online 2018-05-09]

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.

Affiliated researcher

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PubMed 29753646

DOI 10.1016/j.cels.2018.03.010

Crossref 10.1016/j.cels.2018.03.010

S2405-4712(18)30107-8