https://github.com/biocpy/spatialexperiment
Container for Spatial Experiments
https://github.com/biocpy/spatialexperiment
spatial-data
Last synced: about 1 month ago
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Container for Spatial Experiments
- Host: GitHub
- URL: https://github.com/biocpy/spatialexperiment
- Owner: BiocPy
- License: mit
- Created: 2025-01-16T20:22:51.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-02-17T22:12:26.000Z (3 months ago)
- Last Synced: 2025-02-17T22:32:44.156Z (3 months ago)
- Topics: spatial-data
- Language: Python
- Homepage: https://biocpy.github.io/SpatialExperiment/
- Size: 2.67 MB
- Stars: 2
- Watchers: 2
- Forks: 0
- Open Issues: 10
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.txt
- Authors: AUTHORS.md
Awesome Lists containing this project
README
[](https://pypi.org/project/SpatialExperiment/)
# SpatialExperiment
A Python package for storing and analyzing spatial-omics experimental data. `SpatialExperiment` extends [SingleCellExperiment](https://github.com/biocpy/singlecellexperiment) with dedicated slots for image data and spatial coordinates, making it ideal for spatial transcriptomics and other spatially-resolved omics data.
> [!NOTE]
>
> This package is in **active development**.
## Install
To get started, install the package from [PyPI](https://pypi.org/project/SpatialExperiment/)
```bash
pip install spatialexperiment
```
## Usage
The `SpatialExperiment` class extends `SingleCellExperiment` with the following key attributes:
- `spatial_coords`: A BioFrame containing spot/cell spatial coordinates relative to the image, typically including:
- x-coordinates
- y-coordinates
- Additional spatial metadata
- `img_data`: A BiocFrame containing image-related information:
- sample_ids: Unique identifiers for each sample
- image_ids: Unique identifiers for each image
- data: The actual image data
- scale_factor: Scaling factors for proper image interpretation
- `column_data`: Contains sample_id mappings that link spots to their corresponding images
### Quick Start
Here's how to create a SpatialExperiment object from scratch:
```python
from spatialexperiment import SpatialExperiment, construct_spatial_image_class
import numpy as np
from biocframe import BiocFrame
# Create example data
nrows = 200 # Number of features (e.g., genes)
ncols = 500 # Number of spots/cells
# Generate random count data
counts = np.random.rand(nrows, ncols)
# Create feature annotations
row_data = BiocFrame({
"gene_ids": [f"gene_{i}" for i in range(nrows)],
"gene_names": [f"Gene_{i}" for i in range(nrows)]
})
# Create spot/cell annotations
col_data = BiocFrame({
"n_genes": [50, 200] * int(ncols / 2),
"condition": ["healthy", "tumor"] * int(ncols / 2),
"cell_id": [f"spot_{i}" for i in range(ncols)],
"sample_id": ["sample_1"] * int(ncols / 2) + ["sample_2"] * int(ncols / 2),
})
# Generate spatial coordinates
spatial_coords = BiocFrame({
"x": np.random.uniform(low=0.0, high=100.0, size=ncols),
"y": np.random.uniform(low=0.0, high=100.0, size=ncols)
})
# Create image data
img_data = BiocFrame({
"sample_id": ["sample_1", "sample_1", "sample_2"],
"image_id": ["aurora", "dice", "desert"],
"data": [
construct_spatial_image_class("tests/images/sample_image1.jpg"),
construct_spatial_image_class("tests/images/sample_image2.png"),
construct_spatial_image_class("tests/images/sample_image3.jpg"),
],
"scale_factor": [1, 1, 1],
})
# Create SpatialExperiment object
spe = SpatialExperiment(
assays={"counts": counts},
row_data=row_data,
column_data=col_data,
spatial_coords=spatial_coords,
img_data=img_data,
)
```
For more detailed information about available methods and functionality, please refer to the [SingleCellExperiment documentation](https://biocpy.github.io/SingleCellExperiment/).
## Note
This project has been set up using [BiocSetup](https://github.com/biocpy/biocsetup)
and [PyScaffold](https://pyscaffold.org/).