Complex DNA mixture analysis in a forensic context: evaluating the probative value using a likelihood ratio model

Area of Science:

• Forensic Science
• Genetics
• Biotechnology

Background:

• Interpreting mixed DNA profiles from low template DNA (ltDNA) is challenging in forensic casework.
• Stochastic effects like allelic drop-out, drop-in, and stutters complicate ltDNA analysis.
• Newly developed likelihood ratio (LR) models account for these effects, enabling analysis of complex cases.

Purpose of the Study:

• To evaluate the feasibility and relevance of interpreting high-order DNA mixtures (3-5 donors).
• To establish the relative risks of analyzing high-order mixtures by comparing ideal ('gold standard') LRs with casework LRs.
• To guide the implementation of LR interpretation for complex DNA profiles in forensic casework.

Main Methods:

• Utilized experimental samples with known donor genotypes.
• Calculated 'gold standard' LRs with known parameters per contributor.
• Calculated 'casework' LRs assuming unknown donors, estimating parameters from data.
• Employed the basic standard (drop-out/drop-in) model using the LRmix module in R package Forensim.

Main Results:

• Demonstrated the relevance of analyzing high-order DNA mixtures in a forensic context.
• Quantified the risks associated with interpreting complex mixtures.
• Provided insights into the practical application of LR models for challenging DNA profiles.

Conclusions:

• The study advances the understanding of high-order mixture interpretation in forensic science.
• Highlights limitations and provides guidance for implementing LR interpretation in casework.
• Supports the use of advanced LR models for complex DNA profile analysis.