Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet.
IF: 11.091
Cited by: 9


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 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.


Spatial Transcriptomics
data visualization
gene expression
in situ sequencing
network biology
spatial co-expression
spatial transcriptomics

MeSH terms

Breast Neoplasms
Computational Biology
Gene Expression
Gene Expression Profiling
Gene Regulatory Networks
Genes, erbB-2
In Situ Hybridization
Whole Exome Sequencing


Salamon, John
Qian, Xiaoyan
Nilsson, Mats
Lynn, David John

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