Encoding of low-quality DNA profiles as genotype probability matrices for improved profile comparisons, relatedness evaluation and database searches

TL;DR

This paper introduces a novel method for comparing low-quality DNA profiles using genotype probability matrices, enhancing profile comparison, relatedness evaluation, and database searches, especially when samples are degraded or mixed.

Contribution

It presents a new approach that leverages genotype probability distributions, including expert assessments, to improve analysis of complex or low-quality DNA samples.

Findings

More accurate likelihood ratio calculations for degraded DNA

Effective incorporation of relatedness and uncertainty in analysis

Open-source software GPMDNA available for implementation

Abstract

Many DNA profiles recovered from crime scene samples are of a quality that does not allow them to be searched against, nor entered into, databases. We propose a method for the comparison of profiles arising from two DNA samples, one or both of which can have multiple donors and be affected by low DNA template or degraded DNA. We compute likelihood ratios to evaluate the hypothesis that the two samples have a common DNA donor, and hypotheses specifying the relatedness of two donors. Our method uses a probability distribution for the genotype of the donor of interest in each sample. This distribution can be obtained from a statistical model, or we can exploit the ability of trained human experts to assess genotype probabilities, thus extracting much information that would be discarded by standard interpretation rules. Our method is compatible with established methods in simple settings, but is more widely applicable and can make better use of information than many current methods for the analysis of mixed-source, low-template DNA profiles. It can accommodate uncertainty arising from relatedness instead of or in addition to uncertainty arising from noisy genotyping. We describe a computer program GPMDNA, available under an open source license, to calculate LRs using the method presented in this paper.