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ClinBioNGS: A Clinical Bioinformatics Pipeline for Integrated Analysis of Somatic Next-Generation Sequencing Cancer Panels

标杆管理 管道(软件) 计算生物学 工作流程 基因组学 DNA测序 计算机科学 数据挖掘 生物信息学 基因组 精确性和召回率 一致性 RNA序列 基因组浏览器 生物 癌症 精密医学 小贩 排名(信息检索) 基因分型 背景(考古学) 深度测序 序列分析 参考基因组 外显子组 外显子组测序 翻译生物信息学 癌症生物标志物
作者
Raúl Marín,Ania Alay,M Ajenjo,Sara Hijazo‐Pechero,Carla Montironi,E. Hernández-Illán,Pedro Jares,Daniel Azuara,Mar 'Ia Varela,August Vidal,Joan Anton Puig-Butillé,C. Lazaro,Victor Rau Moreno,David Cordero,Ernest Nadal,X. Sole
出处
期刊:JCO clinical cancer informatics [American Society of Clinical Oncology]
卷期号:10 (10): e2500221-e2500221
标识
DOI:10.1200/cci-25-00221
摘要

PURPOSE Somatic next-generation sequencing (NGS) panels are widely used in precision oncology to detect clinically actionable genomic alterations. However, interpreting diverse DNA and RNA alterations remains challenging because of the complexity of tumor-only data and the limitations of current pipelines, which are often proprietary, noncustomizable, or lack visual reports to support clinical interpretation. We present ClinBioNGS, an open-source, panel-agnostic bioinformatics pipeline for the comprehensive analysis of somatic NGS cancer panels in both clinical and translational settings. MATERIALS AND METHODS ClinBioNGS is a modular, fully containerized workflow implemented in Nextflow. It supports integrated analysis of DNA and RNA data, including multicaller small variant detection, copy number alteration (CNA) profiling, gene fusion and splice variant identification, and evaluation of complex genomic biomarkers such as tumor mutational burden and microsatellite instability. Variants are annotated and prioritized using established clinical frameworks. The results are compiled in a self-contained interactive HTML report with dynamic tables and informative visualizations to facilitate clinical interpretation. Validation included SEQC2 reference data sets across six commercial panels, and benchmarking was performed on 2,024 clinical tumor samples analyzed with three commercial platforms. RESULTS ClinBioNGS achieved high accuracy in SEQC2 validation, with precision (0.987-1.000), recall (0.920-0.997), and F1 scores (0.956-0.999) across diverse panels. In a clinical benchmarking with real-world data, the pipeline demonstrated high concordance with commercial solutions for small variants (97%), CNAs (89%), and RNA alterations (94%), while also identifying additional high-confidence alterations missed by vendor pipelines. CONCLUSION ClinBioNGS provides a robust, flexible, and transparent solution for standardized analysis of somatic NGS cancer panels. It supports reproducible, clinically oriented interpretation of genomic data and is freely available for noncommercial research-use only at GitHub.

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