X-CAP

X-CAP is a GBT model that predicts the pathogenicity of single-nucleotide stopgain variants. This repository contains the trained model as well as code to run X-CAP on a VCF file of variants.

Repository structure

• bin: the trained X-CAP model
• data: variants in D_original and D_validation (HGMD variants are only labeled with accession numbers)
• example: demo of X-CAP on chromosome 21 variants in D_validation
• figures: code to generate figures/tables in the paper
• predictions: X-CAP predictions for all stopgains in the human proteome
• src: code to generate X-CAP features and run X-CAP on a VCF file

Setup

1. Create a Conda environment with necessary requirements.

   conda env create --file environment.yml

2. Download ANNOVAR.

Quick usage guide

To run X-CAP on an arbitrary VCF file, use the following command:

  python src/run_xcap.py <input_vcf_file> <reference_vcf_file> <output_dir> <annovar_dir>

1. <input_vcf_file>: Path to VCF file containing the variants of uncertain significance (VUS) which should be scored. X-CAP will score only those variants annotated as stopgains by ANNOVAR and disregard the rest.
2. <reference_vcf_file>: Path to VCF file containing a reference set of known stopgain variants. X-CAP uses these to produce features for variants in the <input_vcf_file>. During evaluation of X-CAP, we used training variants from D_original as the reference set.
3. <output_dir>: Directory where X-CAP results will be written. X-CAP features will be published to <output_dir>/stopgains.features and scores to <outptut_dir>/xcap_scores.vcf.
4. <annovar_dir>: Directory containing the ANNOVAR program. X-CAP uses ANNOVAR to filter out non-stopgain variants.

An illustrative demo can be found in the examples subdirectory.