Shotgun DNA sequencing evidence: Sample-specific and unknown genotyping error probabilities

Many forensic genetic trace samples are of too low quality to obtain short tandem repeat (STR) DNA profiles as the nuclear DNA they contain is highly degraded (e.g., telogen hairs). Instead, performing shotgun DNA sequencing of such samples can provide valuable information on, e.g., single nucleotide polymorphism (SNP) markers. As a result, shotgun sequencing is starting to gain more attention in forensic genetics and statistical models to correctly interpret such evidence, including properly accounting for sequencing errors, are needed. One such model is the wgsLR model by Andersen et. al. (2025) that enabled evaluating the evidential strength of a comparison between the genotypes in the trace sample and reference sample assuming a single-source contribution to both samples. This paper extends the wgsLR model to allow for different (asymmetric) genotyping error probabilities (e.g., from a low quality trace sample and a high quality reference sample). The model was also extended to handle unknown genotyping error probabilities via both maximising profile likelihood and using a prior distribution. It was found that an unknown genotyping error probability of the trace sample could be handled with these methods when having a sufficient number of independent markers and that the results were was robust to different specifications of the prior distribution. The sensitivity of the wgsLR model against overdispersion was also investigated and it was found robust against it. The extensions of the model are implemented in the R package wgsLR.