ArticleBioinformatics (Oxford, England)2023
MoleculeExperiment enables consistent infrastructure for molecule-resolved spatial omics data in bioconductor.
Article in Bioinformatics (Oxford, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- InSituPy: a framework for histology-guided, multi-sample analysis of single-cell spatial omics data.Bioinformatics (Oxford, England) · 2026Article
- Spatially resolved molecular sex differences at single-cell resolution in the adult human ventromedial and arcuate hypothalamus.Cell reports · 2026Article
- Orchestrating Spatial Transcriptomics Analysis with Bioconductor.bioRxiv : the preprint server for biology · 2025Article
- Giotto Suite: a multiscale and technology-agnostic spatial multiomics analysis ecosystem.Nature methods · 2025Article
- Geospatially informed representation of spatial genomics data with SpatialFeatureExperiment.bioRxiv : the preprint server for biology · 2025Article
- SpatialData: an open and universal data framework for spatial omics.Nature methods · 2025Article
- A perspective on FAIR quality control in multiplexed imaging data processing.Frontiers in bioinformatics · 2024Article
- Giotto Suite: a multi-scale and technology-agnostic spatial multi-omics analysis ecosystem.bioRxiv : the preprint server for biology · 2023Article
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4 authors.
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Abstract
motivationImaging-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.
resultsTo 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.
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