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PipeIT2: A tumor-only somatic variant calling workflow for molecular diagnostic Ion Torrent sequencing data
Desiree Schnidrig1, Andrea Garofoli2, Andrej Benjak1
1Department for BioMedical Research, University of Bern, 3008 Bern, Switzerland; SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland.
Genomics
|February 16, 2023
Summary
PipeIT2 identifies cancer-causing somatic mutations without needing healthy DNA samples. This somatic variant calling workflow enhances precision oncology by reliably detecting critical mutations for molecular diagnostics.
Area of Science:
- Genomics
- Bioinformatics
- Cancer Research
Background:
- Precision oncology requires accurate somatic mutation identification.
- Tumor sequencing is common, but matched germline data is often unavailable.
- Existing workflows like PipeIT necessitate germline data for variant filtering.
Purpose of the Study:
- To develop PipeIT2, a somatic variant calling workflow for Ion Torrent data.
- To enable reliable somatic mutation detection without matched germline sequencing.
- To address the clinical need for variant identification in the absence of germline controls.
Main Methods:
- PipeIT2 is a Singularity container-based workflow.
- It processes Ion Torrent sequencing data.
- It is designed for user-friendly execution and reproducibility.
Main Results:
- PipeIT2 achieves >95% recall for variants with variant allele fraction >10%.
- The workflow reliably detects driver and actionable mutations.
- It effectively filters out germline mutations and common sequencing artifacts.
Conclusions:
- PipeIT2 provides accurate somatic mutation identification without germline data.
- Its performance, reproducibility, and ease of use make it suitable for molecular diagnostics.
- This workflow supports clinical decision-making in precision oncology.
