Sepsis, a life-threatening condition resulting from a dysregulated host response to infection, demands timely diagnosis and treatment. Current diagnostic methods, such as culture and antibiotic susceptibility testing, are often time-consuming. Whole-genome sequencing (WGS) of bacterial isolates offers a promising solution for rapid and accurate identification of pathogens and their antimicrobial resistance profiles. This thesis aimed to contribute to the development of improved diagnostic tools for sepsis by analyzing the WGS data of bacterial isolates from patients with community-onset sepsis initially identified as Moraxella infections using MALDI-TOF MS. A comparative analysis was conducted between the WGS data and traditional phenotypic methods. The in-house bioinformatic pipeline employed for WGS analysis involved pre-processing, de novo assembly, quality assessment, and genotypic analysis. JSpeciesWS identified two misidentifications by MALDI-TOF MS. When analysed on CGE ResFinder, resistance genes blaBRO-1 and blaBRO-2 were detected in a significant proportion of Moraxella catarrhalis isolates, but resistance genes were not identified in 13.85% of isolates. MLST analysis revealed a diverse range of sequence types among the analyzed genomes. Furthermore, WGS analysis enabled the detection of some virulence genes associated with Moraxella species. While WGS offers invaluable data for both diagnosis and treatment, the development of faster and more user-friendly bioinformatic pipelines is essential for its widespread adoption in clinical laboratories.