Metadata-Version: 2.1
Name: cy
Version: 0.1.4
Summary: Modelling CRISPR dropout data
Home-page: https://github.com/EmanuelGoncalves/crispy
Author: Emanuel Goncalves
Author-email: eg14@sanger.ac.uk
License: UNKNOWN
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

Crispy
============

Identify associations between genomic alterations (e.g. structural variation, copy-number variation) and CRISPR-Cas9 knockout response.

[Tandem duplications lead to loss of fitness effects in CRISPR-Cas9 data](https://www.biorxiv.org/content/early/2018/05/25/325076)


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 by default each chromosome of each sample independently.


Example
--
```python
import pandas as pd
import crispy as cy

# Import data
data = cy.get_example_data()

# Association analysis
crispy = cy.CRISPRCorrection()\
    .fit_by(by=data['chr'], X=data[['cnv']], y=data['fc'])

# Export
crispy = pd.concat([v.to_dataframe() for k, v in crispy.items()])\
    .sort_values(['cnv', 'k_mean'], ascending=[False, True])

print(crispy)
```


Install
--

```
python setup.py install
```

Enrichment module has Cython files, to compile run:

```
python crispy/enrichment/gsea_setup.py build_ext --inplace
```

Regression module has Cython files, to compile run:

```
python crispy/regression/linear_setup.py build_ext --inplace
```


