CAVA: Clinical Annotation of Variants
|Authors:||Márton Münz, Elise Ruark, Nazneen Rahman, Gerton Lunter|
CAVA (Clinical Annotation of Variants) is a lightweight, fast and flexible Next Generation Sequencing (NGS) variant annotation tool. It implements a clinical sequencing nomenclature (CSN), a fixed variant annotation consistent with the principles of the Human Genome Variation Society (HGVS) guidelines, optimised for automated variant annotation of NGS data. CAVA reports "strand-aware" indel annotations and can flag variants with alternate annotations to facilitate comparisons with other datasets and to highlight those with unclear biological impact.
The tool was formerly called SAVANT (Strand-Aware Variant Annotation Tool).
CAVA has been extensively tested on exome data and is being used in the Mainstreaming Cancer Genetics (MCG) programme which applies NGS to increase the availability and affordability of clinical testing of cancer predisposition genes (CPGs).
|Capabilities:||CAVA reads variants from VCF files and outputs either a VCF or a tab-separated text file with annotations appended to the original input. Variants that can be annotated include SNPs, MNPs and short indels. CAVA can process large files quickly: 1.5 million variants take only an hour to annotate on a 2.9 GHz machine (with the inbuilt multithreading option, one can annotate 6 milion+ VCF records in an hour).|
||Márton Münz, Elise Ruark, Anthony Renwick, Emma Ramsay, Matthew Clarke, Shazia Mahamdallie, Victoria Cloke, Sheila Seal, Ann Strydom, Gerton Lunter, Nazneen Rahman. CSN and CAVA: variant annotation tools for rapid, robust next-generation sequencing analysis in the clinical setting. Genome Medicine 7:76, doi:10.1186/s13073-015-0195-6 (2015).|
|Downloads:||The latest stable version of CAVA can be downloaded from here.|
|The detailed CAVA documentation describing all features of the tool and providing simple use case examples is included in the download above.|
|Dependencies:||CAVA requires Python version 2.7.x (Python 3 is not supported).|
|Installation:||To install CAVA, download and unpack the tgz file and run ./install.sh|
|Running CAVA:||CAVA can be run with the following command:
path/to/cava/cava.py -c config.txt -i input.vcf -o output
You have to specify the configuration file (-c), the input file (-i) and the output file name (-o). See more details in the documentation.
|User Group||Join the CAVA User Group on Google Groups - a forum for discussing bug-reports, feature requests, suggestions or any issues related to CAVA.|
||Please submit all bug reports, comments and feature requests in the CAVA User Group or send any feedback to email@example.com.|