📝 Update docs

gao-lab · Dec 20, 2023 · 8d49e76 · 8d49e76
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diff --git a/.github/workflows/build.yml b/.github/workflows/build.yml
@@ -31,7 +31,7 @@ jobs:
           curl -sSL https://install.python-poetry.org | python3 -
           pip install --upgrade pip
           pip install -e ".[docs, dev]"
-          pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.0+cpu.html
+          pip install pyg_lib torch_scatter==2.1.1 torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.0+cpu.html
       
       - name: Build documentation
         run: |

diff --git a/.github/workflows/release.yml b/.github/workflows/release.yml
@@ -19,10 +19,12 @@ jobs:
 
     - name: Install dependencies
       run: |
+        sudo apt update
+        sudo apt install -y libxml2-utils pandoc
         curl -sSL https://install.python-poetry.org | python3 -
         pip install --upgrade pip
         pip install -e ".[docs, dev]"
-        pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.0+cpu.html
+        pip install pyg_lib torch_scatter==2.1.1 torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.0+cpu.html
 
     
     - name: Build package

diff --git a/README.md b/README.md
@@ -1,13 +1,21 @@
 [![stars-badge](https://img.shields.io/github/stars/gao-lab/SLAT?logo=GitHub&color=yellow)](https://github.com/gao-lab/SLAT/stargazers)
+[![DOI](http://img.shields.io/badge/DOI-10.1038-B31B1B.svg)](https://doi.org/10.1038/s41467-023-43105-5)
 [![dev-badge](https://img.shields.io/endpoint?url=https://gist.githubusercontent.com/xiachenrui/bc835db052fde5bd731a09270b42006c/raw/slat_version.json)](https://gist.github.com/xiachenrui/bc835db052fde5bd731a09270b42006c)
 [![build-badge](https://github.com/gao-lab/SLAT/actions/workflows/build.yml/badge.svg)](https://github.com/gao-lab/SLAT/actions/workflows/build.yml)
 [![license-badge](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 [![docs-badge](https://readthedocs.org/projects/slat/badge/?version=latest)](https://slat.readthedocs.io/en/latest/?badge=latest)
 [![pypi-badge](https://img.shields.io/pypi/v/scslat)](https://pypi.org/project/scslat)
-<!-- [![conda-badge](https://anaconda.org/bioconda/<name>/badges/version.svg)](https://anaconda.org/bioconda/<name>) -->
+
 
 # scSLAT: single cell spatial alignment tools
-**scSLAT** package implements the **SLAT** (**S**patial **L**inked **A**lignment **T**ool) model to align single cell spatial omics data.
+
+<div align="center">
+
+[Installation](#Installation) • [Tutorial](#Tutorial) • [Publication](https://www.nature.com/articles/s41467-023-43105-5)
+
+</div>
+
+**scSLAT** package implements the **SLAT** (**S**patial **L**inked **A**lignment **T**ool) model to align single cell spatial omics data. For more details, please check out our [publication](https://www.nature.com/articles/s41467-023-43105-5).
 
 ![Model architecture](docs/_static/Model.png)
 
@@ -43,18 +51,19 @@ docker pull huhansan666666/slat:0.2.1
 ```
 
 ### PyPI
-> **Note**
+> [!NOTE]
 > Installing `scSLAT` within a new [conda environment](https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html) is recommended.
 
 First, we create a clean environment and install `scSLAT` from PyPI. Then we also need install dependencies for `pyg` manually. We default install with CUDA 11.7. Please refer [here](https://pytorch-geometric.readthedocs.io/en/latest/install/installation.html#quick-start) for CPU version or different CUDA versions.
 
-> **Warning**
+> [!WARNING]
 > old NVIDIA driver may raise error, please update NVIDIA driver to the latest version.
 
 ```bash
 conda create -n scSLAT python=3.8 -y && conda activate scSLAT
 pip install scSLAT
-pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.0+cu117.html
+python -c "import torch; print(torch.__version__)"
+pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.0+cu117.html  # replace torch and CUDA version to yours
 ```
 
 ### Development version
@@ -67,9 +76,6 @@ pip install -e ".[dev,docs]"
 pip install pyg_lib torch_scatter torch_sparse torch_cluster torch_spline_conv -f https://data.pyg.org/whl/torch-2.0.0+cu117.html
 ```
 
-### Conda (Ongoing)
-We plan to provide a conda package of `scSLAT` in the near future.
-
 
 ## Reproduce manuscript results
 1. Please follow the [`env/README.md`](env/README.md) to install all dependencies. Please checkout the repository to v0.2.1 before install `scSLAT`.

diff --git a/docs/tutorials.md b/docs/tutorials.md
@@ -2,6 +2,14 @@
 
 ``SLAT`` has a wide range of application scenarios in spatial alignment, especially in heterogeneous alignment. We provide following tutorials for you to get started with it.
 
+## Pre-match (Recommended)
+We recommend you to pre-match your data before alignment, which can significantly improve the alignment performance.
+
+```{eval-rst}
+.. nbgallery::
+    tutorials/pre_match.ipynb
+```
+
 ## Basic Usage
 
 ### Two slices alignment
@@ -29,12 +37,4 @@ In this tutorial, we focus on finding dynamic regions in embryo development via
 .. nbgallery::
     tutorials/cross_technology.ipynb
     tutorials/times_series.ipynb
-```
-
-## Pre-match (Optional)
-We show how does pre-match function work in this tutorial.
-
-```{eval-rst}
-.. nbgallery::
-    tutorials/pre_match.ipynb
 ```
diff --git a/docs/tutorials/cross_technology.ipynb b/docs/tutorials/cross_technology.ipynb
diff --git a/docs/tutorials/times_series.ipynb b/docs/tutorials/times_series.ipynb
@@ -18,7 +18,15 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Matplotlib created a temporary config/cache directory at /tmp/matplotlib-alvj89z4 because the default path (/home/xiacr/.cache/matplotlib) is not a writable directory; it is highly recommended to set the MPLCONFIGDIR environment variable to a writable directory, in particular to speed up the import of Matplotlib and to better support multiprocessing.\n"
+     ]
+    }
+   ],
    "source": [
     "import os\n",
     "\n",
@@ -48,8 +56,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "adata1 = sc.read_h5ad('E115_Stereo.h5ad')\n",
-    "adata2 = sc.read_h5ad('E125_Stereo.h5ad')"
+    "adata1 = sc.read_h5ad('adata1.h5ad')\n",
+    "adata2 = sc.read_h5ad('adata2.h5ad')"
    ]
   },
   {
@@ -1674,7 +1682,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.13 | packaged by conda-forge | (default, Mar 25 2022, 06:04:18) \n[GCC 10.3.0]"
+   "version": "3.8.0"
   },
   "toc-autonumbering": true,
   "vscode": {

diff --git a/pyproject.toml b/pyproject.toml
@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
 [tool.poetry]
 name = "scSLAT"
 packages = [{include = "scSLAT"}]
-version = "0.2.1"
+version = "0.2.2"
 description = "A graph deep learning based tool to align single cell spatial omics data"
 readme = "README.md"
 license = "MIT"