From dd2b1653c9a99b006708598a3e23b8e6963e4041 Mon Sep 17 00:00:00 2001
From: cobioda <lebrigandk@gmail.com>
Date: Thu, 19 Dec 2024 10:53:08 +0100
Subject: [PATCH] v0.1

---
 README.md | 67 ++++++++++++++++++++++++++++++++++---------------------
 1 file changed, 41 insertions(+), 26 deletions(-)

diff --git a/README.md b/README.md
index 7cebd76..d3f13d9 100644
--- a/README.md
+++ b/README.md
@@ -1,4 +1,16 @@
-# Single-Cell In-Situ python package
+<div align="center">
+
+# **scispy**
+
+**Single-Cell In-Situ Spatial-Omics Data Analysis**
+
+---
+
+<p align="center">
+  <a href="https://scispy.readthedocs.io/en/latest/" target="_blank">Documentation</a>
+  <a href="https://scispy.readthedocs.io/en/latest/notebooks/tutorial.html" target="_blank">Examples</a>
+  <a href="https://www.biorxiv.org/" target="_blank">Preprint</a>
+</p>
 
 [![Tests][badge-tests]][link-tests]
 [![Documentation][badge-docs]][link-docs]
@@ -7,48 +19,51 @@
 [link-tests]: https://github.com/bfxomics/scispy/actions/workflows/test.yml
 [badge-docs]: https://img.shields.io/readthedocs/scispy
 
-scispy is a pthon package for in-situ spatial-omics datasets analysis, mainly developped for vizgen merscope,
-scispy is build on top of spatialdata and spatialdata-io and spatialdata-plot librairies which can handle for
-Nanostring (cosmx) and 10xGenomics (Xenium) experiments.
+</div>
+
+## Background
+
+<p>
+  A pthon package build on top of spatialdata for Single-Cell In-Situ Spatial-Omics data analysis, developped to handle Vizgen (merscope), Nanostring (cosmx) and 10xGenomics (Xenium) experiments.
+</p>
+
+<p align="center">
+  <img src="https://github.com/cobioda/scispy/docs/_static/scispy.png" width="500px">
+</p>
+
+## Features
+
+-   **Read in-situ spatial-omics assays experiments**: build on top of spatialdata package
+-   **Automatic cell type annotation**: scanvi implementation
+-   **Import anatomical .csv shape file from xenium explorer**: as anndata observation
+-   **Automatic run pseudobulk data analysis**: using decoupler and pydeseq2 packages
+-   **Compute cell type proportion in region**: integrating statistical test in case of replicates
+-   **Produce high quality spatial figures**: build on top of spatialdata_plot package
 
 ## Getting started
 
 Please refer to the [documentation][link-docs]. In particular, the
 
 -   [API documentation][link-api].
+-   [Tutorials][link-tutorial]
 
 ## Installation
 
-You need to have Python 3.9 or newer installed on your system.
-
-<!--
-1) Install the latest release of `scispy` from `PyPI <https://pypi.org/project/scispy/>`_:
-
-```bash
-pip install scispy
-```
--->
-
-Install the latest development version:
+1. Create a conda environment (Python >= 3.10)
+2. Install scispy using pip:
 
 ```bash
+conda create -n scispy python==3.10
+conda activate scispy
 pip install git+https://github.com/cobioda/scispy.git@main
 ```
 
-## Release notes
-
-See the [changelog][changelog].
-
-## Contact
-
-For questions and help requests, you can reach out the main developer of this package: in the [kevin lebrigand](mailto:lebrigand@ipmc.cnrs.fr).
-If you found a bug, please use the [issue tracker][issue-tracker].
-
-## Citation
+## Contribution
 
-> preprint available soon
+If you found a bug or you want to propose a new feature, please use the [issue tracker][issue-tracker].
 
 [issue-tracker]: https://github.com/cobioda/scispy/issues
 [changelog]: https://scispy.readthedocs.io/en/latest/changelog.html
 [link-docs]: https://scispy.readthedocs.io
 [link-api]: https://scispy.readthedocs.io/en/latest/api.html
+[link-tutorial]: https://scispy.readthedocs.io/en/latest/notebooks/tutorial.html