From 2aff34e3f52b121d76a23de332833ea4d1f61e0b Mon Sep 17 00:00:00 2001 From: belter Date: Fri, 12 May 2023 09:58:56 +0800 Subject: [PATCH] update README --- README.md | 21 +++++++++++++++------ 1 file changed, 15 insertions(+), 6 deletions(-) diff --git a/README.md b/README.md index b9623c4..b1dcdd7 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,11 @@ -# DeSide +# DeSide: Cellular Deconvolution of Bulk RNA-seq + + +![PyPI version](https://img.shields.io/pypi/v/deside) +![Install with pip](https://img.shields.io/badge/Install%20with-pip-blue) +![MIT](https://img.shields.io/badge/License-MIT-black) + +## What is DeSide? DeSide is a DEep-learning and SIngle-cell based DEconvolution method for solid tumors, which can be used to infer cellular proportions of different cell types from bulk RNA-seq data. @@ -12,7 +19,7 @@ DeSide consists of the following four parts (see figure below): In this repository, we provide the code for implementing these four parts and visualizing the results. -### Requirements +## Requirements DeSide requires Python 3.8 or higher. It has been tested on Linux and MacOS, but should work on Windows as well. - tensorflow>=2.8.0 - scikit-learn==0.24.0 @@ -25,7 +32,7 @@ DeSide requires Python 3.8 or higher. It has been tested on Linux and MacOS, but - bbknn==1.5.1 - SciencePlots -### Installation +## Installation pip should work out of the box: ``` @@ -35,11 +42,11 @@ conda activate deside pip install deside ``` -### Documentation +## Documentation Documentation is available either in the source tree (doc/), or online. (will be available soon) -### Usage Examples +## Usage Examples Usage examples can be found: [DeSide_mini_example](https://github.com/OnlyBelter/DeSide_mini_example) Three examples are provided: @@ -47,5 +54,7 @@ Three examples are provided: - Training a model from scratch - Generating a synthetic dataset -### License +## License DeSide can be used under the terms of the MIT License. + +## Citation