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

Abstract

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. The sensitivity of the wgsLR model against overdispersion was also investigated and it was found robust against it. It was also found that handling an unknown genotyping error probability of the trace sample with the methods having a sufficient number of independent markers gave concordant weight of evidence (WoE) under both the hypotheses (same or different individuals being donors of trace and reference sample). It was found more conservative to use a too small trace sample genotyping error probability rather than a too high genotyping error probability as the latter can explain genotype inconsistencies by errors rather than due to two different individuals being the donors of the trace sample and reference sample. The extensions of the model are implemented in the R package wgsLR.