A command-line tool for filtering, extracting, and prioritizing genetic variants from VCF files. VariantCentrifuge combines gene-centric region extraction, multi-tier filtering (bcftools, SnpSift, pandas), inheritance analysis, and configurable scoring into a single reproducible pipeline.
- Gene-centric variant extraction using gene names or BED regions
- Three-tier filtering: bcftools prefilter, SnpSift expressions, pandas final filter
- Inheritance pattern analysis (de novo, AD, AR, X-linked, compound het)
- Configurable variant scoring models
- Gene burden analysis with Fisher's exact test
- Interactive HTML reports with sortable tables and IGV.js integration
- ClinVar, gnomAD, and SpliceAI annotation links
- Cohort aggregation across multiple samples
- Field profiles for switching annotation database versions (e.g., dbNSFP v4/v5)
- Docker image with all bioinformatics dependencies included
- Stage-based pipeline architecture with parallel execution (
--use-new-pipeline)
Docker (recommended -- all tools included):
docker pull ghcr.io/scholl-lab/variantcentrifuge:latestpip:
pip install variantcentrifugeFrom source:
git clone https://github.com/scholl-lab/variantcentrifuge.git
cd variantcentrifuge && pip install .External tools (bcftools, snpEff, SnpSift, bedtools) must be in PATH when not using Docker.
Install via conda: mamba create -y -n vc bcftools snpsift snpeff bedtools
# Filter rare coding variants in a gene list
variantcentrifuge \
--gene-file genes.txt \
--vcf-file input.vcf.gz \
--preset rare,coding \
--html-report \
--xlsx
# Score and filter with a custom model
variantcentrifuge \
--gene-file genes.txt \
--vcf-file input.vcf.gz \
--preset rare,coding \
--scoring-config-path scoring/nephro_variant_score \
--final-filter 'score > 0.8 and IMPACT == "HIGH"' \
--output-file results.tsvA Snakemake 8+ workflow for batch-processing multiple VCFs on HPC clusters (SLURM, PBS) is included under workflow/, with cluster profiles in profiles/ and sample configuration in config/.
See scripts/run_snakemake.sh for the auto-detecting launcher.
Full documentation: scholl-lab.github.io/variantcentrifuge
Contributions are welcome. Please see the Contributing Guide for details.
If you use VariantCentrifuge in your research, please cite:
Citation information will be added upon publication.
This project is licensed under the MIT License.