Metadata-Version: 2.1
Name: isv
Version: 0.2.0
Summary: Automated Interpretation of Structural Copy Number Variants
Home-page: UNKNOWN
Author: Tomas Sladecek
Author-email: tomas.sladecek@geneton.sk
License: UNKNOWN
Keywords: python,machine learning,copy number variation
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Software Development :: Build Tools
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.6, <4
Description-Content-Type: text/markdown
License-File: LICENSE.txt

# ISV package

Python package for easy prediction of pathogenicity of annotated Copy Number Variants (CNVs)

The package contains two functions:

### 1. isv.predict(X_raw, cnv_type)
- returns an array of probabilities

### 2. shap_values(X_raw, cnv_type)
- calculates shap values for given CNVs

---
Both functions assume that input dataframes contain counts of following genomic elements:
```     
[
    'gencode_genes',
    'protein_coding',
    'pseudogenes',
    'mirna',
    'lncrna',
    'rrna',
    'snrna',
    'morbid_genes',
    'disease_associated_genes',
    'hi_genes',  # ONLY FOR LOSSES
    'regions_HI',  # ONLY FOR LOSSES
    'regions_TS',  # ONLY FOR GAINS
    'regulatory',
    'regulatory_enhancer',
    'regulatory_open_chromatin_region',
    'regulatory_promoter',
    'regulatory_promoter_flanking_region',
    'regulatory_ctcf_binding_site',
    'regulatory_tf_binding_site',
    'regulatory_curated'
]
```

