Automated Interpretation of Structural Copy Number Variants
Project description
ISV package
Python package for easy prediction of pathogenicity Copy Number Variants (CNVs)
Requirements
xgboost>=1.4.2
shap>=0.39.0
sklearn-json>=0.1.0
numba>=0.53.1
numpy>=1.20.3
pandas>=1.2.4
numba>=0.53.1
The package might work with older versions, however above specified versions are recommended.
Make sure to install these packages before installing the isv
package
The package contains three functions:
1. isv.annotate(cnvs)
- annotates cnvs provided in a list, np.array or pandas DataFrame format represented in 4 columns:
chromosome
,start (grch38)
,end (grch38)
andcnv_type
- Returns an annotated dataframe which can be used as an input to following two functions
2. isv.predict(X_raw, cnv_type, proba)
- returns an array of isv predictions
3. isv.shap_values(X_raw, cnv_type)
- calculates shap values for given CNVs
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