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. 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.
Original language | English |
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Pages (from-to) | 626-630.e3 |
Journal | Cell Systems |
Volume | 6 |
Issue number | 5 |
DOIs | |
Publication status | Published or Issued - 23 May 2018 |
Keywords
- Cytoscape
- data visualization
- gene expression
- in situ sequencing
- network biology
- spatial co-expression
- spatial transcriptomics
ASJC Scopus subject areas
- Pathology and Forensic Medicine
- Histology
- Cell Biology