In this thesis, I applied a genomics-based approach using different methodological strategies to analyse challenging forensic samples to generate reliable DNA data. The aim was to evaluate the utility of MPS in forensic genetics and explore alternative analytical strategies for improved DNA recovery. In Paper I, STRs were analysed to generate a quality-assured allele frequency reference database for the Swedish population. Paper II evaluated microhaplotypes, demonstrating robust performance when analysing degraded DNA and complex mixtures. In Paper III, I applied an extended SNP panel (FORCE) in combination with unique molecular indices (UMIs), which improved genotype accuracy and increased sensitivity. Quality-assured genotypes were recovered from casework-like samples, highlighting the potential for distant kinship inference from low-template and degraded material. Paper IV demonstrated that assays targeting large SNP sets and whole-genome datasets can recover extensive and reliable genetic information when analysing DNA samples of limited quantity and challenging quality. In addition, I showed that alternative data interpretation strategies based on genotype likelihoods were highly efficient for obtaining reliable results from sparse sequencing data.
Taken together, these studies show that genomics-based MPS strategies can substantially enhance the recovery, accuracy, and interpretability of forensic DNA data. The findings from this thesis provide methodological guidance for integrating MPS in casework to increase the resolution of forensic investigations.