Curated molecular oncology watch for solid tumors

ClairS is a novel deep-learning method specifically designed for calling somatic small variants in tumor-normal pairs using long-read sequencing data. Unlike most existing tools optimized for short reads, ClairS was trained on synthetic somatic variants and real cancer cell lines. The method demonstrated high accuracy, achieving F1 scores of 96.19% for SNVs and 79.67% for indels after training augmentation. The authors emphasize that improved read phasing enabled by long-read sequencing is key to accurate SNV detection, especially at low variant allele fractions. ClairS is presented as a robust and reliable open-source caller.