Combined Variant Effect Predictors
Project description
Pre-requisite
Python 2.7
matplotlib (http://matplotlib.org)
Installation
To install this module, run the following commands:
sudo python setup.py install
Download reference database
After the installation is complete, type
CombiVEP_reference_updater
This application will automatically check with UCSC and LJB database, and see if it is required to download the new one. The original database size is around 1GB each. The total operation time for each database should be around 30-60 mins.
Training
After having reference database installed, the CombiVEP model can be trained using
CombiVEP_trainer <training_data_file>
<training_data_file> must be in CBV format: CHROM, POS, REF, ALT, ACTUAL_DELETERIOUS_EFFECT. Each field is separated by a tab. SNP Position(POS) is 1-based index. The VariBench training data file in CBV format can be found at
combivep/data/CBV/training.cbv
Prediction
To use the trained model to predict the effect, you can do it using
CombiVEP_predictor <input_file> [-F FORMAT]
The input file can be either in VCF or above CBV format. Default is in VCF format. So if you want to use input file in VCF format, simply type
CombiVEP_predictor <vcf_file>
If you to do the prediction using file in CBV format, you can
CombiVEP_predictor <cbv_file> -F CBV
The VariBench test data file in CBV format can be found at
combivep/data/CBV/test.cbv
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