Abstract
Motivation Spatially resolved transcriptomics is a new set of technologies to measure gene expression for up to thousands of genes at near-single-cell, single-cell, or sub-cellular resolution, together with the spatial positions of the measurements. Analyzing combined molecular and spatial information has generated new insights about biological processes that manifest in a spatial manner within tissues. However, to efficiently analyze these data, specialized data infrastructure is required, which facilitates storage, retrieval, subsetting, and interfacing with downstream tools.
Results Here, we describe SpatialExperiment, a new data infrastructure for storing and accessing spatially resolved transcriptomics data, implemented within the Bioconductor framework in the R programming language. SpatialExperiment extends the existing SingleCellExperiment for single-cell data from the Bioconductor framework, which brings with it advantages of modularity, interoperability, standardized operations, and comprehensive documentation. We demonstrate the structure and user interface with examples from the 10x Genomics Visium and seqFISH platforms. SpatialExperiment is extendable to alternative technological platforms measuring expression and to new types of data modalities, such as spatial immunofluorescence or proteomics, in the future. We also provide access to example datasets and visualization tools in the STexampleData, TENxVisiumData, and ggspavis packages.
Availability and Implementation SpatialExperiment is freely available from Bioconductor at https://bioconductor.org/packages/SpatialExperiment. The STexampleData, TENxVisiumData, and ggspavis packages are available from GitHub and will be submitted to Bioconductor.
Competing Interest Statement
The authors have declared no competing interest.
