CBIcall: a configuration-driven framework for variant calling in large sequencing cohorts

Clicks: 3
ID: 324960
2026
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Abstract
Abstract Motivation Variant calling for next-generation sequencing (NGS) data relies on a diverse ecosystem of tools and workflows. Large-scale collaborative studies increasingly adopt federated analysis, where each institution processes sensitive data locally using standardized pipelines. Deploying identical pipelines across multiple centers remains challenging because heterogeneous software environments and computing policies can cause workflow divergence and inconsistent results. Results We developed CBIcall, a workflow-agnostic, configuration-driven framework that runs standardized variant-calling pipelines from raw FASTQ files to analysis-ready VCFs using a single YAML file. An execution driver validates user parameters, enforces compatibility across pipelines, analysis modes, work-flow backends, genome builds, and tool versions, and records structured provenance for each run, ensuring consistent and reproducible pipeline execution across computing environments. CBIcall dispatches validated workflows through Bash or Snakemake backends and provides production-ready pipelines for germline WES, WGS (single-sample or cohort joint genotyping following GATK Best Practices), and mitochondrial DNA analysis. We validated CBIcall on public datasets and deployed it in the EU HEREDITARY project, processing 1,111 samples with both WES and mtDNA pipelines on an institutional HPC system, demonstrating its suitability for reproducible cohort-scale genomic analyses. Availability and implementation CBIcall is open source (GPLv3) and distributed with ready-to-run pipelines; full dependency and installation documentation is available at https://github.com/CNAG-Biomedical-Informatics/cbicall .
Reference Key
openalex_W7140311339 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Manuel Rueda, Dietmar Fernandez Orth, Ivo G Gut
Journal Bioinformatics advances
Year 2026
DOI
10.1093/bioadv/vbag232
URL
https://doi.org/10.1093/bioadv/vbag232
Keywords Keywords not found

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