Metadata-Version: 2.1
Name: cy
Version: 0.2.2
Summary: Modelling CRISPR dropout data
Home-page: https://github.com/EmanuelGoncalves/crispy
Author: Emanuel Goncalves
Author-email: eg14@sanger.ac.uk
License: UNKNOWN
Description: ![Crispy logo](images/logo.png)
        
        [![License](https://img.shields.io/badge/License-BSD%203--Clause-blue.svg)](https://opensource.org/licenses/BSD-3-Clause) [![PyPI version](https://badge.fury.io/py/cy.svg)](https://badge.fury.io/py/cy)
        
        Method to correct gene independent copy-number effects on CRISPR-Cas9 screens.
        
        
        Description
        --
        Crispy uses [Sklearn](http://scikit-learn.org/stable/index.html) implementation of [Gaussian Process Regression](http://scikit-learn.org/stable/modules/generated/sklearn.gaussian_process.GaussianProcessRegressor.html#sklearn.gaussian_process.GaussianProcessRegressor), fitting each sample independently.
        
        Install
        --
        
        ```
        pip install cy
        ```
        
        Example
        --
        ```python
        import crispy as cy
        import matplotlib.pyplot as plt
        
        # Import data
        rawcounts, copynumber = cy.Utils.get_example_data()
        
        # Import CRISPR-Cas9 library
        lib = cy.Utils.get_crispr_lib()
        
        # Instantiate Crispy
        crispy = cy.Crispy(
            raw_counts=rawcounts, copy_number=copynumber, library=lib
        )
        
        # Fold-changes and correction integrated funciton.
        # Output is a modified/expanded BED formated data-frame with sgRNA and segments information
        bed_df = crispy.correct(x_features='ratio', y_feature='fold_change')
        print(bed_df.head())
        
        # Gaussian Process Regression is stored
        crispy.gpr.plot(x_feature='ratio', y_feature='fold_change')
        plt.show()
        
        ```
        ![GPR](/images/example_gp_fit.png)
        
        
        Credits and License
        --
        Developed at the [Wellcome Sanger Institue](https://www.sanger.ac.uk/) (2017-2018).
        
        For citation please refer to: [biorxiv pre-print](https://www.biorxiv.org/content/early/2018/05/25/325076)
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Description-Content-Type: text/markdown
