Metadata-Version: 2.1
Name: pypairs
Version: 2.0.5
Summary: A Python-reimplementation of the Pairs algorithm described by A. Scialdone et al. (2015)
Home-page: https://github.com/rfechtner/pypairs
Author: Ron Fechtner
Author-email: ronfechtner@gmail.com
License: https://github.com/rfechtner/pypairs/blob/master/LICENSE
Project-URL: Original Paper, http://dx.doi.org/10.1016/j.ymeth.2015.06.021
Project-URL: GitHub URL, https://github.com/rfechtner/pypairs
Description: # PyPairs - A python scRNA-Seq classifier
        
        This is a python-reimplementation of the _Pairs_ algorithm as described by A. Scialdone et. al. (2015).
        Original Paper available under: https://doi.org/10.1016/j.ymeth.2015.06.021
        
        The algorithm aims to classify single cells based on their transcriptomic signal. Initially created to predict cell
        cycle phase from scRNA-Seq data, this algorithm can be used for various applications.
        
        It is a supervised maschine learning algorithm and as such it consits of two components: 
        training (sandbag) and prediction (cyclone)
        
        ## Getting Started
        
        These instructions will get you a copy of the project up and running on your local machine for development and testing 
        purposes. 
        
        ### Installation
        
        This package is hosted at PyPi (https://pypi.org/project/pypairs/) and can be installed on any system running Python3 
        with:
        
        ```
        python3 -m pip install pypairs
        ```
        
        ### Minimal example
        
        Assuming you have two scRNA count files (csv, columns = samples, rows = genes) and one annotation file (csv, no header, 
        two rows: "gene, class") a minimal example would look like this:
        
        ```
        from pypairs import wrapper
        
        trainings_matrix = [PATH TO MATRIX]
        annotation = [PATH TO ANNOTATION]
        testing_matrix = [PATH TO MATRIX]
        
        marker_pairs = wrapper.sandbag_from_file(trainings_matrix, annotation)
        
        prediction = wrapper.cyclone_from_file(testing_matrix, marker_pairs)
        ```
        
        ## Core Dependencis
        
        * [Numpy](http://www.numpy.org/) 
        * [Numba](https://numba.pydata.org/)
        * [Pandas](https://pandas.pydata.org/)
        * [Scanpy](https://github.com/theislab/scanpy)
        
        ## Authors
        
        * **Antonio Scialdone** - *original algorithm*
        * **Ron Fechtner** - *implementation and extension in Python*
        
        ## License 
        
        This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details
Keywords: scRNA classifier machine-learning marker pairs
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3 :: Only
Provides-Extra: plot
