| Literature DB >> 29753646 |
John Salamon1, Xiaoyan Qian2, Mats Nilsson2, David John Lynn3.
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: Cytoscape; data visualization; gene expression; in situ sequencing; network biology; spatial co-expression; spatial transcriptomics
Mesh:
Year: 2018 PMID: 29753646 DOI: 10.1016/j.cels.2018.03.010
Source DB: PubMed Journal: Cell Syst ISSN: 2405-4712 Impact factor: 10.304