Low-coverage sequencing is increasingly used in forensic genetics due to its cost-efficiency and ability to process degraded samples. However, calculating forensic likelihood ratios (LRs) from such data introduces challenges due to increased uncertainty in genotype calling. This approach requires advanced probabilistic models to quantify the weight of evidence accurately, accounting for allele dropouts, sequencing errors, and population genetics parameters. Improving LR estimation under low coverage enhances the reliability of forensic DNA evidence in criminal investigations.
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