Linked-read analysis identifies mutations in single-cell DNA sequencing data

Whole-genome sequencing of DNA from single cells has the potential to reshape our understanding of the mutational heterogeneity in normal and disease tissues. A major difficulty, however, is distinguishing artifactual mutations that arise from DNA isolation and amplification from true mutations. Here, we describe linked-read analysis (LiRA), a method that utilizes phasing of somatic single nucleotide variants with nearby germline variants to identify true mutations, thereby allowing accurate estimation of somatic mutation rates at the single cell level.