Onkopipe

Onkopipe performs comprehensive detection and reporting of single nucleotide variations (SNVs), copy number variations (CNVs), and structural variations (SVs) from tumor sequencing data to support molecular profiling and precision oncology.


Key Features:

  • Variant Detection: Detects single nucleotide variations (SNVs), copy number variations (CNVs), and structural variations (SVs) for molecular profiling in clinical settings.
  • Unified Output Format: Integrates quality control, read alignment, BAM pre-processing, and variant calling and consolidates variants into Variant Call Format (VCF) for downstream analysis.
  • Containerization: Uses containerization to ensure reproducibility and consistency across computational environments.
  • Parallelization and Customization: Supports parallel processing to accelerate large datasets and provides customizable pipeline configurations.
  • Validation and Accuracy: Demonstrated high accuracy and concordance in variant detection through rigorous validation.

Scientific Applications:

  • Molecular tumor boards: Supports molecular tumor boards and clinical workflows requiring precise genetic profiling.
  • Tumor profiling without matched normal controls: Enables comprehensive analysis of tumor samples without matched normal controls to facilitate personalized treatment strategies in precision oncology.

Methodology:

Performs quality control, read alignment, BAM pre-processing, variant calling, and consolidation of variants into VCF; employs containerization and parallel processing and has undergone rigorous validation demonstrating high concordance.

Topics

Details

Cost:
Free of charge
Tool Type:
workflow
Operating Systems:
Mac, Linux, Windows
Added:
3/18/2024
Last Updated:
11/24/2024

Operations

Data Inputs & Outputs

Copy number variation detection

Publications

Yang J, Beißbarth T, Dönitz J. Onkopipe: A Snakemake Based DNA-Sequencing Pipeline for Clinical Variant Analysis in Precision Medicine. Studies in Health Technology and Informatics. 2023. doi:10.3233/shti230694. PMID:37697838.