Bioinformatics · 2023 · 13 citations · 15 references
Life SciencesCell BiologyMolecular BiologyComputational BiologyMolecular Cell BiologyTranscriptomicsCellular ImagingOmics Data IntegrationSingle-cell GenomicsSingle-cell TranscriptomicsSpatial Single-cell AnalysisSpatial TranscriptomicsCell SegmentationData StandardsImage-based Spatial OmicsImage-based TranscriptomicsResearch Data InfrastructureSingle-cell Resolution Spatial ProfilingSpatial Cell SegmentationSpatially Resolved Transcriptomics
MOTIVATION: Imaging-based spatial transcriptomics (ST) technologies have achieved subcellular resolution, enabling detection of individual molecules in their native tissue context. Data associated with these technologies promise unprecedented opportunity toward understanding cellular and subcellular biology. However, in R/Bioconductor, there is a scarcity of existing computational infrastructure to represent such data, and particularly to summarize and transform it for existing widely adopted computational tools in single-cell transcriptomics analysis, including SingleCellExperiment and SpatialExperiment (SPE) classes. With the emergence of several commercial offerings of imaging-based ST, there is a pressing need to develop consistent data structure standards for these technologies at the individual molecule-level. RESULTS: To this end, we have developed MoleculeExperiment, an R/Bioconductor package, which (i) stores molecule and cell segmentation boundary information at the molecule-level, (ii) standardizes this molecule-level information across different imaging-based ST technologies, including 10× Genomics' Xenium, and (iii) streamlines transition from a MoleculeExperiment object to a SpatialExperiment object. Overall, MoleculeExperiment is generally applicable as a data infrastructure class for consistent analysis of molecule-resolved spatial omics data. AVAILABILITY AND IMPLEMENTATION: The MoleculeExperiment package is publicly available on Bioconductor at https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html. Source code is available on Github at: https://github.com/SydneyBioX/MoleculeExperiment. The vignette for MoleculeExperiment can be found at https://bioconductor.org/packages/release/bioc/html/MoleculeExperiment.html.
15
Dictionary learning for integrative, multimodal and scalable single-cell analysis
Yuhan Hao, Tim Stuart, Madeline H. Kowalski et al. · Nature Biotechnology · 2023 · 4.8K citations · Full text
A mesoscale connectome of the mouse brain
Seung Wook Oh, Julie A. Harris, Lydia Ng et al. · Nature · 2014 · 2.9K citations · Full text
Squidpy: a scalable framework for spatial omics analysis
Giovanni Palla, Hannah Spitzer, Michal Klein et al. · Nature Methods · 2022 · 1.1K citations · Full text
A high-resolution transcriptomic and spatial atlas of cell types in the whole mouse brain
Zizhen Yao, Cindy T. J. van Velthoven, Michael Kunst et al. · Nature · 2023 · 1.1K citations · Full text