A clustering algorithm for the single cell analysis of mixtures

A probabilistic clustering algorithm is proposed for the analysis of forensic DNA mixtures in which individual cells are isolated and short tandem repeats are amplified using the polymerase chain reaction to generate single cell electropherograms. The task of the algorithm is to use the peak height information in the electropherograms to group the cells according to their contributors. Using a recently developed experimental set of individual cell electropherograms, a large set of simulations shows that the proposed clustering algorithm has excellent performance in correctly grouping single cells, and for assigning likelihood ratios for persons of interest (of known genotype).