Stereopy - Spatial Transcriptomics Analysis in Python

Stereopy is a fundamental and comprehensive tool for mining and visualization based on spatial transcriptomics data, such as Stereo-seq (spatial enhanced resolution omics sequencing) data. More analysis will be added here, either from other popular tools or developed by ourselves, to meet diverse requirements. Meanwhile, we are still working on the improvement of performance and calculation efficiency.

• Get quickly started by browsing Usage Principles, Tutorials or API.

• Open to discuss and provide feedback on Github.

• Follow changes in Release Notes.

News

The paper of Stereopy has been pre-printed on bioRxiv!

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics.

Highlights

• More suitable for performing downstream analysis of Stereo-seq data.

• Support efficient reading and writing (IO), pre-processing, and standardization of multiple spatial transcriptomics data formats.

• Self-developed Gaussian smoothing model, tissue and cell segmentation algorithm models, and cell correction algorithm.

• Integrate various functions of dimensionality reduction, spatiotemporal clustering, cell clustering, spatial expression pattern analysis, etc.

• Develop interactive visualization functions based on features of Stereo-seq workflow.

Workflow

Latest Additions

Version 1.6.2

1.6.2 : 2025-11-20

BUG Fixes:

1. Fixed a crash issue in st.io.read_gef when reading GEF files with a gene expression level larger than 4 x 10⁹.

2. Fixed a crash issue in st.io.read_gef when reading GEF files larger than 30 GB.

3. Fixed missing exon data when saving mid-results to a GEF file using st.io.write_mid_gef after analysis.

4. Fixed inconsistent cellid in the output when generating a Loom file via st.tools.generate_loom, ensuring they now match those in the source GEF/GEM files.

5. Fixed an error in st.tools.generate_loom when processing .tissue.gef files generated by the SAW-ST-V8 pipeline.

Version 1.6.1

1.6.1 : 2025-06-16

Features:

1. st.io.stereo_to_anndata supports adding multiple images.

2. st.plt.batches_umap supports downloading.

BUG Fixes:

1. Pinned the version of fastcluster in dependencies to 1.2.6 for ensuring installation compatibility.

2. Fixed the problem that the width and height of the images added to AnnData by st.io.stereo_to_anndata were swapped.

3. Fixed the problem that the order of bins is different in GEM and GEF under a same data.

Version 1.6.0

1.6.0 : 2025-02-21

Features:

1. Addition of new algorithm Spatialign for batch effect removal.

Version 1.5.1

1.5.1 : 2024-12-26

Features:

1. st.io.stereo_to_anndata supports adding image information into the converted AnnData object.

2. h5ad2rds.R supports adding image information into the converted RDS file.

3. Optimized the visualization of the plotting scale for spatial scatter plot when inputting small data.

BUG Fixes:

1. Fixed the problem that the layers was lost when converting StereoExpData to AnnData by using st.io.stereo_to_anndata.

2. Fixed the problem that the result of st.tl.gen_ccc_micro_envs cannot be reproduced.