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

IF: 11.091

Cited by: 9

Abstract

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.

Keywords

Spatial Transcriptomics

ISS

Cytoscape

data visualization

gene expression

in situ sequencing

network biology

spatial co-expression

spatial transcriptomics

MeSH terms

Algorithms

Breast Neoplasms

Computational Biology

Computers

Gene Expression

Gene Expression Profiling

Gene Regulatory Networks

Genes, erbB-2

Humans

In Situ Hybridization

Software

Whole Exome Sequencing

Authors

Salamon, John

Qian, Xiaoyan

Nilsson, Mats

Lynn, David John

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