Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

We developed a comprehensive bioinformatic workflow, called the PTA Analysis Toolbox (PTATO), to accurately detect single base substitutions, insertions-deletions (indels) and structural variants in PTA-based WGS data. PTATO includes a machine learning approach and filtering based on recurrency to distinguish PTA-artefacts from true mutations with high sensitivity (up to 90%), outperforming existing bioinformatic approaches. Our results show that PTATO enables studying somatic mutagenesis in the genomes of single cells with unprecedented sensitivity and accuracy.