Interpretation of complex DNA profiles using empirical models and a method to measure their robustness

Area of Science:

• Forensic Science
• Genetics
• Biostatistics

Background:

• Complex DNA profiles present interpretation challenges in forensic casework.
• Stutter alleles can be indistinguishable from minor contributors in DNA mixtures.
• Existing methods may not adequately address dropout and contamination in low copy number (LCN) DNA analysis.

Purpose of the Study:

• To develop a new protocol for interpreting complex DNA profiles using likelihood ratios.
• To apply a conservative and widely applicable framework to conventional DNA cases.
• To enhance the robustness of DNA evidence reporting by including probabilities of misleading evidence.

Main Methods:

• Integration of low copy number (LCN) interpretation framework, including dropout and contamination probabilities.
• Treatment of stutter alleles as real alleles by increasing potential contributors to the DNA profile.
• Application of a case-specific 'Tippett' test to qualify likelihood ratios with robustness parameters.

Main Results:

• A new methodology for reporting complex DNA profiles using conservative likelihood ratio calculations.
• Successful application of LCN interpretation framework to conventional DNA cases, accounting for stutters.
• Development of robustness parameters to assess the probability of misleading evidence.

Conclusions:

• The proposed method provides a robust approach to interpreting complex DNA profiles, even with challenging artefacts like stutters.
• The methodology can be explained in a user-friendly manner for court presentations.
• The framework is extensible for ranked likelihood ratio (LR) searches in DNA databases.