add logfoldchanges #1

LICENSE

@@ -1,21 +1,29 @@
-MIT License
+BSD 3-Clause License
 
-Copyright (c) 2020 Min Dai
+Copyright (c) 2021, Min Dai
+All rights reserved.
 
-Permission is hereby granted, free of charge, to any person obtaining a copy
-of this software and associated documentation files (the "Software"), to deal
-in the Software without restriction, including without limitation the rights
-to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
-copies of the Software, and to permit persons to whom the Software is
-furnished to do so, subject to the following conditions:
+Redistribution and use in source and binary forms, with or without
+modification, are permitted provided that the following conditions are met:
 
-The above copyright notice and this permission notice shall be included in all
-copies or substantial portions of the Software.
+1. Redistributions of source code must retain the above copyright notice, this
+   list of conditions and the following disclaimer.
 
-THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
-IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
-FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
-AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
-LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
-OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
-SOFTWARE.
+2. Redistributions in binary form must reproduce the above copyright notice,
+   this list of conditions and the following disclaimer in the documentation
+   and/or other materials provided with the distribution.
+
+3. Neither the name of the copyright holder nor the names of its
+   contributors may be used to endorse or promote products derived from
+   this software without specific prior written permission.
+
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
+AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
+IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
+DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
+FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
+DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
+SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
+CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
+OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
+OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

README.rst

@@ -1,3 +1,12 @@
+|Stars| |PyPI| |Docs| 
+
+.. |Stars| image:: https://img.shields.io/github/stars/genecell/COSG?logo=GitHub&color=yellow
+   :target: https://github.com/genecell/COSG/stargazers
+.. |PyPI| image:: https://img.shields.io/pypi/v/cosg?logo=PyPI
+   :target: https://pypi.org/project/cosg
+.. |Docs| image:: https://readthedocs.org/projects/cosg/badge/?version=latest
+   :target: https://cosg.readthedocs.io
+
 Accurate and fast cell marker gene identification with COSG
 =======================================================================================================
 
@@ -9,12 +18,16 @@ COSG is a cosine similarity-based method for more accurate and scalable marker g
 - Marker genes or genomic regions identified by COSG are more indicative and with greater cell-type specificity.
 - COSG is ultrafast for large-scale datasets, and is capable of identifying marker genes for one million cells in less than two minutes.
 
-The method and benchmarking results are described in `Dai et al., (2021)`_.
+The method and benchmarking results are described in `Dai et al., (2021)`_. 
+
+Documentation
+--------------
+The documentation for COSG is available `here <https://cosg.readthedocs.io/en/latest/>`_.
 
 Tutorial
 ---------
 
-The `COSG tutorial <https://cosg.readthedocs.io/en/latest/tutorials/COSG-tutorial.ipynb>`_ provides a quick-start guide for using COSG and demonstrates the superior performance of COSG as compared with other methods.
+The `COSG tutorial <https://nbviewer.jupyter.org/github/genecell/COSG/blob/main/tutorials/COSG-tutorial.ipynb>`_ provides a quick-start guide for using COSG and demonstrates the superior performance of COSG as compared with other methods, and the `Jupyter notebook <https://github.com/genecell/COSG/blob/main/tutorials/COSG-tutorial.ipynb>`_ is also available.
 
 Question
 ---------
@@ -26,3 +39,4 @@ If COSG is useful for your research, please consider citing `Dai et al., (2021)`
 
 .. _Dai et al., (2021): https://www.biorxiv.org/content/10.1101/2021.06.15.448484v1
 
+