@article {1449929, title = {Identification of somatic mutations in single cell DNA sequencing data using a spatial model of allelic imbalance}, journal = {Nature Communications}, volume = {10}, number = {1}, year = {2019}, pages = {3908}, abstract = {Recent advances in\ single\ cell\ technology have enabled dissection of cellular heterogeneity in great detail. However,\ analysis\ of\ single\ cell\ DNA sequencing\ data\ remains challenging due to bias and artifacts that arise during\ DNA\ extraction and whole-genome amplification, including\ allelic imbalance\ and dropout. Here, we present a framework for statistical estimation of allele-specific amplification\ imbalance\ at any given position in\ single\ cell\ whole-genome\ sequencing\ data\ by utilizing the allele frequencies of heterozygous\ single\ nucleotide polymorphisms in the neighborhood. The resulting\ allelic imbalance\ profile is critical for determining whether the variant allele fraction of an observed\ mutation\ is consistent with the expected fraction for a true variant. This method, implemented in SCAN-SNV (Single\ Cell\ ANalysis\ of SNVs), substantially improves the\ identification\ of\ somatic\ variants in\ single\ cells. Our allele balance framework is broadly applicable to genotype\ analysis\ of any variant type in any\ data\ that might exhibit\ allelic imbalance.}, author = {Luquette, Joe L. and Bohrson, Craig L. and Sherman, Max and Park,Peter J. } }