This article describes an adaption of Bright et al.’s work modeling peak height variability in CE-DNA profiles to the modeling of allelic aSTR (autosomal short tandem repeats) read counts from NGS-DNA profiles, specifically for profiles generated from the ForenSeq™ DNA Signature Prep Kit, DNA Primer Mix B.
Bright et al.’s model consists of three key components within the estimation of total allelic product—template, locus-specific amplification efficiencies, and degradation. The current work investigated the two mass parameters—template and locus-specific amplification efficiencies—and used MLE (maximum likelihood estimation) and MCMC (Markov chain Monte Carlo) methods to obtain point estimates to calculate the total allelic product. The expected read counts for alleles were then calculated after proportioning some of the expected stutter product from the total allelic product. Due to preferential amplicon selection introduced by the sample purification beads, degradation is difficult to model from the aSTR outputs alone. Improved modeling of the locus-specific amplification efficiencies may mask the effects of degradation. Although this model could be improved by introducing locus specific variances in addition to locus specific priors, current results demonstrate the suitability of adapting Bright et al.’s allele peak height model for NGS-DNA profiles. This model could be incorporated into continuous probabilistic interpretation approaches for mixed DNA profiles. (publisher abstract modified)
- Expert Algorithm for Substance Identification (EASI) using Mass Spectrometry: Statistical Foundations in Unimolecular Reaction Rate Theory
- Mapping the Cyberstalking Landscape: An Empirical Analysis of Federal U.S. Crimes
- A comparison of statistical models for the analysis of complex forensic DNA profiles