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GeneSurfer Enables Transcriptome-wide Exploration and Functional Annotation of Gene Co-expression Modules in 3D Spatial Transcriptomics Data.
Li, Chang; Thijssen, Julian; Kroes, Thomas; van der Burg, Ximaine; van der Weerd, Louise; Höllt, Thomas; Lelieveldt, Boudewijn.
Afiliação
  • Li C; Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.
  • Thijssen J; Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.
  • Kroes T; Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.
  • van der Burg X; Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.
  • van der Weerd L; Department of Radiology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.
  • Höllt T; Department of Human Genetics, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands.
  • Lelieveldt B; Computer Graphics and Visualization, INSY, TU Delft, 2628 XE Delft, The Netherlands.
bioRxiv ; 2024 Jul 07.
Article em En | MEDLINE | ID: mdl-39005368
ABSTRACT
Gene co-expression provides crucial insights into biological functions, however, there is a lack of exploratory analysis tools for localized gene co-expression in large-scale datasets. We present GeneSurfer, an interactive interface designed to explore localized transcriptome-wide gene co-expression patterns in the 3D spatial domain. Key features of GeneSurfer include transcriptome-wide gene filtering and gene clustering based on spatial local co-expression within transcriptomically similar cells, multi-slice 3D rendering of average expression of gene clusters, and on-the-fly Gene Ontology term annotation of co-expressed gene sets. Additionally, GeneSurfer offers multiple linked views for investigating individual genes or gene co-expression in the spatial domain at each exploration stage. Demonstrating its utility with both spatial transcriptomics and single-cell RNA sequencing data from the Allen Brain Cell Atlas, GeneSurfer effectively identifies and annotates localized transcriptome-wide co-expression, providing biological insights and facilitating hypothesis generation and validation.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda País de publicação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Holanda País de publicação: Estados Unidos