iScienceBioinformaticsPeer-reviewed journal article
GeneSurfer Enables Transcriptome-wide Exploration and Functional Annotation of Gene Co-expression Modules in 3D Spatial Transcriptomics Data
Chang LiiD, Julian ThijsseniD, Thomas KroesiD, Ximaine R. van der BurgiD, Louise van der WeerdiD, Thomas HölltiD, Boudewijn P. F. LelieveldtiD
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.
- organism: human
- assay: spatial transcriptomics
- assay: bulk RNA-seq
- research focus: cell type annotation
- research focus: clustering
- research focus: gene regulatory network inference
- research focus: database / resource
- approach: statistical model
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- 8th percentile
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