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VariantCentrifuge

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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.

Features

  • 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
  • Modular association testing: SKAT-O, COAST allelic series, logistic/linear burden regression with covariates and PCA, ACAT-O omnibus combination — see the Association Testing Guide
  • Interactive HTML reports with column-level filtering, semantic color badges, summary dashboard, accessible design (WCAG 2.1 AA), and PDF export
  • 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

Installation

Docker (recommended -- all tools included):

docker pull ghcr.io/scholl-lab/variantcentrifuge:latest

The production image contains an immutable runtime environment. pip is used only while building the image and is removed before distribution; package installation belongs in a development environment.

pip:

pip install variantcentrifuge

From 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

Quick Start

# 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.tsv

Snakemake Workflow

A 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.

Documentation

Full documentation: scholl-lab.github.io/variantcentrifuge

Contributing

Contributions are welcome. Please see the Contributing Guide for details.

How to cite

If you use VariantCentrifuge in your research, cite the software and record the exact release or commit used in your analysis. CITATION.cff provides machine-readable citation metadata for GitHub's Cite this repository menu. Until an archive DOI is available, cite the corresponding GitHub release or commit URL. For example, for the latest published release:

Popp, B. (2026). VariantCentrifuge (version 0.17.12) [Computer software]. https://github.com/scholl-lab/variantcentrifuge/releases/tag/v0.17.12

The current development version is 0.21.0, as recorded in variantcentrifuge/version.py, CITATION.cff, and .zenodo.json. It has no release date yet; the latest published release is v0.17.12 (2026-07-19). For a development checkout, include its full commit hash and URL instead of citing it as a published release.

Zenodo archive pending: metadata is prepared, but no DOI has been minted. See the release and archival guide for the maintainer steps to archive a release and add the resulting DOI badge.

License

This project is licensed under the MIT License.

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