This study investigates the analyses and clustering of Campylobacter spp., Listeria monocytogenes and Shiga toxin-producing Escherichia coli (STEC) at Livsmedelsverket. Livsmedelsverket is a control authority in Sweden. They work with eating habits, what food contains and safe food and good drinking water, where outbreak investigations of the above-mentioned bacterial types is a part of the work. For the investigations Livsmedelsverket uses a pipeline that is written in the programming language Python. The purpose of this project is to add identification of virulence genes and analysis of the STEC bacterium to the script. But also to develop the existing method to be able to cluster more isolates without losing information, enable the user to adjust parameters in the pipeline and write an ethical analysis to the work that is done. Our study shows the analysis and clustering of the three different types of bacteria, clustering of the samples from the analysis, both adaptively and statically, and that it can determine serotype, sequence type and virulence genes. We therefore conclude that STEC can be added to outbreak investigations at Livsmedelsverkets in-house pipeline. The clustering method has also been modified to be able to use more of the information given from the samples with the restriction of having lower accuracy.