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Network Visualization and Analysis of Spatially Aware Gene Expression Data with InsituNet
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab). Uppsala University, Sweden.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab). Uppsala University, Sweden.
Number of Authors: 42018 (English)In: Cell Systems, ISSN 2405-4712, Vol. 6, no 5, p. 626-630Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2018. Vol. 6, no 5, p. 626-630
Keywords [en]
network biology, data visualization, in situ sequencing, gene expression, Cytoscape, spatial transcriptomics, spatial co-expression
National Category
Biological Sciences
Identifiers
URN: urn:nbn:se:su:diva-157730DOI: 10.1016/j.cels.2018.03.010ISI: 000433906700011PubMedID: 29753646OAI: oai:DiVA.org:su-157730DiVA, id: diva2:1236505
Available from: 2018-08-02 Created: 2018-08-02 Last updated: 2018-08-02Bibliographically approved

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