SpatialData to Xenium Explorer

Converting any SpatialData object into files that can be opened by the Xenium Explorer.

Check the documentation to get started quickly.

Xenium Explorer is a registered trademark of 10x Genomics

You may also be interested in a pipeline for spatial-omics that uses this package: see Sopa.

Installation

Requirement: python>=3.9

pip install spatialdata_xenium_explorer

Features

• Conversion of the following data: images, cell boundaries (polygons or spot), transcripts, cell-by-gene table, and cell categories (or observations).
• Image alignment can be made on the Xenium Explorer, and then the SpatialData object can be updated
• When working on the SpatialData or AnnData object, new cell categories can be easily and quickly added to the Explorer
• When selecting cells with the "lasso tool" on the Explorer, it's easy to select back these cells on the SpatialData or AnnData object

Usage

You can use our CLI or API, see examples below. It will create up to 6 files, among which a file called experiment.xenium. Double-click on this file to open it on the Xenium Explorer (make sure you have the latest version of the software).

CLI

spatialdata_xenium_explorer write /path/to/sdata.zarr

Check our documentation for more details.

API

import spatialdata
import spatialdata_xenium_explorer

sdata = spatialdata.read_zarr("...")

spatialdata_xenium_explorer.write("/path/to/directory", sdata, image_key, shapes_key, points_key, gene_column)

Check our documentation for more details.

Contributing

This package is still in early development. Contributions are welcome (new issues, pull requests, ...).

Cite us

This library has been detailed in a more general article spatial omics analysis, see the Sopa library. The latter article is not published yet, but you can cite our preprint:

@article {Blampey2023.12.22.571863,
	author = {Quentin Blampey & Kevin Mulder et al.},
	title = {Sopa: a technology-invariant pipeline for analyses of image-based spatial-omics},
	elocation-id = {2023.12.22.571863},
	year = {2023},
	doi = {10.1101/2023.12.22.571863},
	publisher = {Cold Spring Harbor Laboratory},
	URL = {https://www.biorxiv.org/content/early/2023/12/23/2023.12.22.571863},
	eprint = {https://www.biorxiv.org/content/early/2023/12/23/2023.12.22.571863.full.pdf},
	journal = {bioRxiv}
}