Changed readme for readthedocs

README.rst

@@ -0,0 +1,62 @@
+.. image:: https://badge.fury.io/py/sccellfie.svg
+   :target: https://pypi.org/project/sccellfie/
+
+.. image:: https://github.com/earmingol/scCellFie/actions/workflows/tests.yml/badge.svg
+   :alt: test-sccellfie
+
+.. image:: https://codecov.io/gh/earmingol/scCellFie/graph/badge.svg?token=22NENAKNKI
+   :target: https://codecov.io/gh/earmingol/scCellFie
+
+.. image:: https://pepy.tech/badge/sccellfie/month
+   :target: https://pepy.tech/project/sccellfie
+
+Single-cell CellFie is a computational tool for studying metabolic tasks using Python, inspired by the original implementation of
+`CellFie <https://github.com/LewisLabUCSD/CellFie>`_, another tool originally developed in MATLAB by the `Lewis Lab <https://lewislab.ucsd.edu/>`_. This version is designed to be
+compatible with single-cell and spatial data analysis using Scanpy, while including a series of improvements and new analyses.
+
+.. image:: https://github.com/earmingol/scCellFie/blob/main/scCellFie-Logo.png?raw=true
+   :alt: Logo
+   :width: 350
+   :height: 350
+   :align: center
+
+This image was created with the assistance of DALL·E
+
+Installation
+----------
+
+To install scCellFie, use pip::
+
+    pip install sccellfie
+
+Features
+--------
+
+- **Single cell and spatial data analysis:** Tailored for analysis of metabolic
+  tasks using fully single cell resolution and in space.
+
+- **Speed:** This implementation further leverages the original CellFie. It is now memory
+  efficient and run much faster! A dataset of ~70k single cells can be analyzed in ~5 min.
+
+- **New analyses:** From marker selection of relevant metabolic tasks to integration with
+  inference of cell-cell communication.
+
+- **User-friendly:** Python-based for easier use and integration into existing workflows.
+
+- **Scanpy compatibility:** Fully integrated with Scanpy, the popular single cell
+  analysis toolkit.
+
+Acknowledgments
+---------------
+
+This implementation is inspired by the original `CellFie tool <https://github.com/LewisLabUCSD/CellFie>`_ developed by
+the `Lewis Lab <https://lewislab.ucsd.edu/>`_. Please consider citing their work if you find this tool useful:
+
+- **Model-based assessment of mammalian cell metabolic functionalities using omics data**.
+  *Cell Reports Methods, 2021*. https://doi.org/10.1016/j.crmeth.2021.100040
+
+- **ImmCellFie: A user-friendly web-based platform to infer metabolic function from omics data**.
+  *STAR Protocols, 2023*. https://doi.org/10.1016/j.xpro.2023.102069
+
+- **Inferring secretory and metabolic pathway activity from omic data with secCellFie**.
+  *Metabolic Engineering, 2024*. https://doi.org/10.1016/j.ymben.2023.12.006

setup.py

@@ -14,8 +14,8 @@
     author='Erick Armingol',
     author_email='[email protected]',
     description="A tool for studying metabolic tasks from single-cell and spatial transcriptomics",
-    long_description=open('README.md').read(),
-    long_description_content_type='text/markdown',
+    long_description=open('README.rst').read(),
+    long_description_content_type='text/x-rst',
     url='https://github.com/earmingol/scCellFie',
     packages=find_packages(),
     install_requires=[