- SYN-Y2-2025-015: Publication [Fragkouli et al., The Centre for Research & Technology Hellas]
- bioRxiv, October 2025. Read here>
- Somatic variant calling lacks high-quality ground truth datasets, making tool evaluation difficult. To address this, the authors developed synth4bench, a synthetic data pipeline that generates controlled benchmarking datasets. Using these data, we systematically evaluated five tumor-only variant callers (Mutect2, FreeBayes, VarDict, VarScan2, LoFreq) across varying sequencing conditions. The results show substantial inconsistencies between callers and a strong dependence on sequencing depth and read length. Indels remain the most challenging variants, particularly at low allele frequencies. Caller performance reflected underlying algorithmic choices: the most robust tools showed superior precision in allele frequency estimates, while the most sensitive maximized true-positive detection. The weakest performer displayed systematic errors and the lowest overall accuracy. Overall, no single caller fits all scenarios; optimal sequencing design and careful tool selection are essential. The variability observed also indicates that current algorithms still fall short of fully modeling the complexity of mutational processes.
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