Modeling allelic analyte signals for aSTRs in NGS DNA profiles

Area of Science:

• Forensic Science
• Genetics
• Bioinformatics

Background:

• Modeling peak height variability is crucial for interpreting DNA profiles.
• Previous models focused on capillary electrophoresis (CE-DNA) profiles.
• Next-generation sequencing (NGS-DNA) generates complex allelic read count data.

Purpose of the Study:

• To adapt Bright et al.'s peak height variability model for autosomal short tandem repeat (aSTR) read counts from NGS-DNA profiles.
• To investigate template and locus-specific amplification efficiencies in NGS-DNA data.
• To assess the suitability of the adapted model for forensic DNA analysis.

Main Methods:

• Adaptation of Bright et al.'s model for NGS-DNA profiles.
• Utilized maximum likelihood estimation (MLE) and Markov chain Monte Carlo (MCMC) methods.
• Investigated template and locus-specific amplification efficiencies.

Main Results:

• The adapted model successfully estimates total allelic product and expected read counts.
• Improved modeling of locus-specific amplification efficiencies may mitigate degradation effects.
• Demonstrated the suitability of the adapted model for NGS-DNA profiles.

Conclusions:

• The adapted model shows promise for interpreting NGS-DNA profiles, particularly for autosomal short tandem repeats (aSTR).
• This approach can be integrated into continuous probabilistic interpretation methods for complex mixed DNA profiles.
• Further improvements could involve incorporating locus-specific variances and priors.