Conbase: A software for unsupervised discovery of clonal somatic mutations in single cells through read phasing

Abstract

Accurate variant calling and genotyping represent major limiting factors for downstream applications of single-cell genomics. Here, we report Conbase for the identification of somatic mutations in single-cell DNA sequencing data. Conbase leverages phased read data from multiple samples in a dataset to achieve increased confidence in somatic variant calls and genotype predictions. Comparing the performance of Conbase to three other methods, we find that Conbase performs best in terms of false discovery rate and specificity and provides superior robustness on simulated data, in vitro expanded fibroblasts and clonal lymphocyte populations isolated directly from a healthy human donor.