CAPICE: a computational method for Consequence-Agnostic Pathogenicity Interpretation of Clinical Exome variations

CAPICE is a computational method for predicting the pathogenicity of SNVs and InDels. It is a gradient boosting tree model trained using a variety of genomic annotations used by CADD score and trained on the clinical significance. CAPICE performs consistently across diverse independent synthetic, and real clinical data sets. It ourperforms the current best method in pathogenicity estimation for variants of different molecular consequences and allele frequency.

Input format: The input file needs to be an valid VCF file. An example input file. For now, the maximum size of input is 10k variants, otherwise the input file might be truncated.

Source code can be found in the github repository.

Precomputed scores can be found in the zenodo repository.

Manuscript can be found in medRxiv.

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