DNA mixture interpretation based on the continuous model

Abstract

In forensic science, the interpretation of DNA mixture proˆles and small amounts or degraded DNA proˆles is challenging due to di‹culties in evaluating the contribution of the person of interest ( e.g., victim and suspect ) . In recent years, some probabilistic genotyping software programs based on a continuous model were developed to promote the interpretation of complex DNA proˆles. The model uses quantitative information of peak heights in the DNA proˆle and considers the eŠect of stutters and allelic drop-out. Therefore, the model is eŠective for interpreting complex DNA proˆles, and some software based on the model that has been applied to actual caseworks. This review provides the concept of probabilistic genotyping based on a continuous model. We explain calculation principles of likelihood ratios, weight values, and expected peak heights in the continuous model. We also discuss the current issues of software validation, management of artifact peaks, and the estimation of the number of contributors.