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

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.

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.

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.

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.