Literature DB >> 29753646

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

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.
Copyright © 2018 Elsevier Inc. All rights reserved.

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


  5 in total

1.  Spatial and temporal localization of immune transcripts defines hallmarks and diversity in the tuberculosis granuloma.

Authors:  Berit Carow; Thomas Hauling; Xiaoyan Qian; Igor Kramnik; Mats Nilsson; Martin E Rottenberg
Journal:  Nat Commun       Date:  2019-04-23       Impact factor: 14.919

2.  Spatially visualized single-cell pathology of highly multiplexed protein profiles in health and disease.

Authors:  Mayar Allam; Thomas Hu; Shuangyi Cai; Krishnan Laxminarayanan; Robert B Hughley; Ahmet F Coskun
Journal:  Commun Biol       Date:  2021-05-27

3.  Hybridization-based in situ sequencing (HybISS) for spatially resolved transcriptomics in human and mouse brain tissue.

Authors:  Daniel Gyllborg; Christoffer Mattsson Langseth; Xiaoyan Qian; Eunkyoung Choi; Sergio Marco Salas; Markus M Hilscher; Ed S Lein; Mats Nilsson
Journal:  Nucleic Acids Res       Date:  2020-11-04       Impact factor: 16.971

4.  Matisse: a MATLAB-based analysis toolbox for in situ sequencing expression maps.

Authors:  Sergio Marco Salas; Daniel Gyllborg; Christoffer Mattsson Langseth; Mats Nilsson
Journal:  BMC Bioinformatics       Date:  2021-07-31       Impact factor: 3.169

5.  A multiple network-based bioinformatics pipeline for the study of molecular mechanisms in oncological diseases for personalized medicine.

Authors:  Serena Dotolo; Anna Marabotti; Anna Maria Rachiglio; Riziero Esposito Abate; Marco Benedetto; Fortunato Ciardiello; Antonella De Luca; Nicola Normanno; Angelo Facchiano; Roberto Tagliaferri
Journal:  Brief Bioinform       Date:  2021-11-05       Impact factor: 11.622

  5 in total

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