%0 Journal Article
%T Linked-read analysis identifies mutations in single-cell DNA-sequencing data
%J -
%D 2019
%R https://doi.org/10.1038/s41588-019-0366-2
%X Whole-genome sequencing of DNA from single cells has the potential to reshape our understanding of mutational heterogeneity in normal and diseased tissues. However, a major difficulty is distinguishing amplification artifacts from biologically derived somatic mutations. Here, we describe linked-read analysis (LiRA), a method that accurately identifies somatic single-nucleotide variants (sSNVs) by using read-level phasing with nearby germline heterozygous polymorphisms, thereby enabling the characterization of mutational signatures and estimation of somatic mutation rates in single cells
%U https://www.nature.com/articles/s41588-019-0366-2