spatialdataR

spatialdataR provides an R interface to Python's spatialdata framework. It enables the representation, handling, and integration of diverse spatial omics datasets using the OME-NGFF (Next Generation File Format) standard. For more details on the framework, see Marconato et al. (2024).

Resources

• SpatialData class documentation.
• SpatialData.plot: Visualization capabilities.
• SpatialData.data: Example SpatialDatasets.
• SpatialData.demo: Biotechnology workflows.

Key features

• Out-of-memory handling of images and labels using ZarrArray (via the Rarr package).
• Points and shapes are managed using duckdb-backed tables.
• Functional annotations (e.g., gene expression) are represented as SingleCellExperiment objects, integrated via anndataR.
• A system for mapping data across multiple coordinate spaces, including support for transformation graphs.

Installation

The package is available through Bioconductor:

if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("spatialdataR")

Quick Start

library(spatialdataR)
zs <- system.file("extdata", "blobs.zarr", package="spatialdataR")
(sd <- readSpatialData(zs))

class: SpatialData   
- images(2):
  - blobs_image (3,64,64)
  - blobs_multiscale_image (3,64,64)
- labels(2):
  - blobs_labels (64,64)
  - blobs_multiscale_labels (64,64)
- points(1):
  - blobs_points (200)
- shapes(3):
  - blobs_circles (5,circle)
  - blobs_multipolygons (2,polygon)
  - blobs_polygons (5,polygon)
- tables(1):
  - table (3,10) [blobs_labels]
coordinate systems(5):
- global(8): blobs_image
  blobs_multiscale_image ... blobs_polygons
  blobs_points
- scale(1): blobs_labels
- translation(1): blobs_labels
- affine(1): blobs_labels
- sequence(1): blobs_labels

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Past and current contributors include (in alphabetical order): Vince Carey, Helena L. Crowell, Louise Deconinck, Yixing E. Dong, Hugo Gruson, Samuel Gunz, Artür Manukyan, Dario Righelli, Charlotte Soneson, Michael Stadler.