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

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. Salamon et al. present InsituNet, a software application that converts spatially resolved in situ transcriptomics data into interactive network-based visualizations. InsituNet enables the statistical analysis of spatial co-expression between transcripts and can uncover how spatial co-expression profiles change in different regions of the tissue or across different tissue sections.