Probabilistic Analysis for Next Generation Sequencing (PANGS)

In the field of DNA forensic analysis, capillary electrophoresis (CE) is slowly giving way to newer Next Generation Sequencing (NGS) approaches for genotyping which can collect more information in a single workflow than was previously possible. When considering forensic samples from multiple individuals containing trace amounts of DNA (<100 pg) such as those from a steering wheel or hand gun, specialized probabilistic genotyping software to required make use of full use of the data. Currently there is no such software which is capable of working with NGS data. In order to address this urgent need, ChromoLogic LLC (CL) proposes to develop a Probabilistic Analysis for Next Generation Sequencing (PANGS) system based on a continuous Bayesian probability model that incorporates read counts, mixture ratios, and artifacts such as allele drop-in, drop-out, stutter, and degradation. The PANGS system is comprised of three main subsystems: (i) a preprocessing subsystem that prepares and processes raw NGS and CE data; (ii) a Bayesian probabilistic model which is used to perform deconvolution and calculate likelihood ratios; and, (iii) a reporting subsystem that prepares an easy-to-understand report of the analysis.