Genome biology · 2021 · 950 citations · 54 references
Life SciencesBioinformaticsCell BiologyData VisualizationGene Expression AnalysisTranscriptomicsCell-type-specific TranscriptomicsCellular VisualizationSingle-cell Data VisualizationSingle-cell TranscriptomicsSingle-cell VisualizationSpatial TranscriptomicsCell Type ResolutionInteractive Single-cell Data ExplorationMicroenvironment InteractionsProteomic Data AnalysisSingle-cell Resolution Spatial ProfilingSpatial EnrichmentSpatial Gene Expression PatternsSpatial Transcriptomics Visualization
Spatial transcriptomic and proteomic technologies enable investigation of cells within their native microenvironment. The authors present Giotto, an open‑source toolbox for spatial data analysis and visualization. Giotto offers end‑to‑end spatial analysis, integrating single‑cell RNA‑seq for cell‑type enrichment and interactive visualization, validated across diverse datasets.
Abstract Spatial transcriptomic and proteomic technologies have provided new opportunities to investigate cells in their native microenvironment. Here we present Giotto, a comprehensive and open-source toolbox for spatial data analysis and visualization. The analysis module provides end-to-end analysis by implementing a wide range of algorithms for characterizing tissue composition, spatial expression patterns, and cellular interactions. Furthermore, single-cell RNAseq data can be integrated for spatial cell-type enrichment analysis. The visualization module allows users to interactively visualize analysis outputs and imaging features. To demonstrate its general applicability, we apply Giotto to a wide range of datasets encompassing diverse technologies and platforms.
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