.. Stereopy manual documentation master file, created by sphinx-quickstart on Mon Nov 21 18:07:00 2022. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. .. ===================== .. Document Title .. ===================== .. First level .. ----------- .. Second level .. ++++++++++++ .. Third level .. ************ .. Fourth level .. ~~~~~~~~~~~~ |stars| |pypi| |downloads| |docs| 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 `_. Upcoming functions -------------------- * Batch Effect removal funciton * ... 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 ---------- .. image:: ./_static/Stereopy_workflow_v1.0.0.png :alt: Title figure :width: 700px :align: center Latest Additions ------------------ Version 1.3.1 ~~~~~~~~~~~~~~~~~~~ 1.3.1 : 2024-06-28 Features: 1. Addition of new method **'adaptive'** for `st.tl.get_niche `_ (the original method is named **'fixed'**). 2. Changed some parameter names of `st.tl.filter_cells `_ and `st.tl.filter_genes `_ for eliminating ambiguity(old parameter names are still compatible). 3. Filter the results of **PCA** and **UMAP** simultaneously when running `st.tl.filter_cells`. BUG Fixes: 1. Fixed the problem that `ms_data.to_isolated` is incompatible with that there are duplicate **cell names** in different samples. 2. Fixed the problem that `st.io.read_gef` is incompatible with those **GEF** files that contain **gene names** ending with **'_{number}'** (like **'ABC_123'**). 3. Upgraded **gefpy** to latest for fixing the error that **gene names** are lost after running **CellCorrection**. Version 1.3.0 ~~~~~~~~~~~~~~~~~~~ 1.3.0 : 2024-05-31 Features: 1. Addition of `MSData.tl.st_gears `_ for spatial alignment of **Multi-sample**. 2. `High Resolution Matrix Export `_ can support both **GEF** and **GEM** files. 3. Addition of parameters `min_count` and `max_count` for `st.tl.filter_genes `_. 4. `MSData.integrate `_ can be compatible with sparse matrix when `MSData.var_type` is `union`. 5. Addition of `MSData.tl.set_scope_and_mode `_ to set `scope` and `mode` globally on **Multi-sample** analysis. 6. Addition of `MSData.plt.ms_spatial_scatter `_ to plot spatial scatter plot for each **sample** in **Multi-sample** separately. BUG Fixes: 1. Fixed the problem that `st.io.read_gem` is incompatible with **GEM** files containing **geneID**. 2. Fixed the bug of losing part of metadata when writing **StereoExpData** / **MSData** into **Stereo-h5ad** or **h5ms** file. 3. Fixed the incompatibility problem with **AnnData** when performing `st.tl.sctransform`. Version 1.2.0 ~~~~~~~~~~~~~~~~~~~ 1.2.0 : 2024-03-30 Features: 1. `st.io.read_gem` and `st.io.read_gef` support expression matrix files with geneID information. 2. Analysis results of `find_marker_genes` will be saved into the output AnnData h5ad. 3. Upgraded tissue segmentation algorithm. 4. Addition of `st.tl.adjusted_rand_score` to calculate the adjusted Rand coefficient between two clusters. 5. Addition of `st.tl.silhouette_score` to calculate the average silhouette coefficient of a cluster. 6. `h5ad2rds.R` is compatible with AnnData version > 0.7.5, to convert from h5ad to rds files. 7. Addition of the clustering category labels to the graph of `st.plt.paga_compare`. BUG Fixes: 1. Fixed the error of high memory consumption when converting `X.raw` into AnnData. .. toctree:: :titlesonly: :maxdepth: 3 :hidden: content/00_Installation content/01_Usage_principles Tutorials(Multi-sample)/Multi_sample Tutorials/index content/03_API content/04_Community content/05_Contributing content/06_Release_notes content/07_References .. |docs| image:: https://img.shields.io/static/v1?label=docs&message=stereopy&color=green :target: https://stereopy.readthedocs.io/en/latest/index.html :alt: docs .. |stars| image:: https://img.shields.io/github/stars/STOmics/stereopy?logo=GitHub&color=yellow :target: https://github.com/STOmics/stereopy :alt: stars .. |downloads| image:: https://static.pepy.tech/personalized-badge/stereopy?period=total&units=international_system&left_color=grey&right_color=blue&left_text=downloads :target: https://pepy.tech/project/stereopy :alt: Downloads .. |pypi| image:: https://img.shields.io/pypi/v/stereopy :target: https://pypi.org/project/stereopy/ :alt: PyPI