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

IF 2.6 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Bioinformatics advances Pub Date : 2026-08-12 eCollection Date: 2026-01-01 DOI:10.1093/bioadv/vbag232
Manuel Rueda, Dietmar Fernandez-Orth, Ivo G Gut
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引用次数: 0

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 backend-flexible, configuration-driven framework that runs standardized variant-calling pipelines from raw FASTQ files to analysis-ready VCFs. Users define each analysis in a single YAML parameters file, which CBIcall resolves against a controlled workflow registry and resource catalog. The execution driver validates parameters and checks compatibility among pipelines, analysis modes, workflow backends, genome builds, tool versions, and resource bundles. CBIcall supports reproducibility auditing by comparing executions using recorded provenance and output fingerprints. CBIcall dispatches validated workflows natively through Bash, Cromwell, Nextflow and 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 evaluated analytical performance using public benchmark datasets and validated reproducibility across four computing environments. We further deployed CBIcall in the EU HEREDITARY project, where it processed 1102 samples with both WES and mtDNA pipelines on an institutional HPC system, supporting 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.

CBIcall:一个配置驱动的框架,用于在大型测序队列中调用变体。
动机:下一代测序(NGS)数据的变体呼唤依赖于工具和工作流程的多样化生态系统。大规模协作研究越来越多地采用联合分析,每个机构使用标准化管道在本地处理敏感数据。跨多个中心部署相同的管道仍然具有挑战性,因为异构的软件环境和计算策略可能导致工作流分歧和不一致的结果。结果:我们开发了CBIcall,这是一个工作流程后端灵活、配置驱动的框架,它运行标准化的变量调用管道,从原始FASTQ文件到分析就绪的vcf。用户在单个YAML参数文件中定义每个分析,CBIcall根据受控的工作流注册表和资源目录解析该文件。执行驱动程序验证参数并检查管道、分析模式、工作流后端、基因组构建、工具版本和资源包之间的兼容性。CBIcall通过使用记录的来源和输出指纹来比较执行,从而支持再现性审计。CBIcall通过Bash、Cromwell、Nextflow和snake makake后端本地调度经过验证的工作流程,并为种系WES、WGS(单样本或队列联合基因分型,遵循GATK最佳实践)和线粒体DNA分析提供生产就绪的管道。我们使用公共基准数据集评估了分析性能,并验证了四种计算环境的可重复性。我们进一步在欧盟遗传项目中部署了CBIcall,在一个机构HPC系统上使用WES和mtDNA管道处理了1102个样本,支持其可重复队列规模基因组分析的适用性。可用性和实现:CBIcall是开源的(GPLv3),并通过随时可运行的管道分发;完整的依赖关系和安装文档可在https://github.com/CNAG-Biomedical-Informatics/cbicall上获得。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.60
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