 Hello everyone, I'm Berbo Gatsun, the buyer of my X-Pass from at SenSano and today I will give a short presentation on our Galaxy Instance. Our Galaxy Instance is available at galaxy.senSano.be. It is free to use but you need to register and account to use it. The Instance is focused on microbial genomics for which we offer a set of tools from the toolsheds as well as tools that we have implemented ourselves. We offer an extensive framework for microbial genomics enabling analysis such as QC gene detection, sequence typing, snip calling phylogenies and so on. As an example, I represent the analysis of 6 mycopacterium tuberculosis isolates collected in 2019 in Belgium. In TrueGalaxy, I investigate how these samples are related to each other and also check their AMR profiles using the workflow schematically represented below. Evidently, this is just an example and there are much more possibilities as each of these tools function as a building block. The first step in the workflow is quality control for which we offer several tools including some frequently used ones from the toolsheds such as FastQC and Quest. But we also offer a set of custom wrappers around tools such as confinder and check-in offering a complete QC toolbox. Secondly, we will perform regular MST typing with our custom MST tool. It performs a little detection using KMA but we also offer the same functionality with BlastPaste and Azure State2-based detection. Currently, we offer 46 MST-CG MST schemes but novel schemes are added upon request. All of these databases are updated automatically every weekend. The output of the tool is provided as an interactive HTML report which can be viewed from within Galaxy. The report contains fairyland sections starting with the analysis info at the top. The second section contains FastQC reports and statistics for the re-trimming which can be enabled or disabled in the tool interface. The third section contains the output of the typing itself in this case the sequence type and the corresponding allele calls. At the bottom of the report there is a section containing the commands that were used to obtain the results. In this case, these are the commands for Tremomatic and KMA. As all six isolates were classified as sequence type 215 I repeated the analysis with the Core Genome MST scheme from PubMST containing 744 low side and the resulting output was used as input for MST tree tool. This tool takes MST output files for several samples and generates the corresponding phylogenetic tree in various formats. And as you can see in this network representation three of the six samples also have identical CGMST profiles. Therefore, I start another analysis with a SNP phylogeny tool. This is also a custom tool that takes FastQ inputs in a reference genome to perform a complete SNP-based phylogenetic analysis. The tool starts by SNP calling and filtering using either SAM tools or CFSAM and the resulting SNP matrix is used as input for automatic model selection and tree building with MEGA. The output of this tool is also provided as an interactive HTML report. The top of the report contains the output of the re-trimming which can be browsed interactively. Then we have a table with some statistics such as the sequencing depth, the mapping rates, and the number of SNPs which can also be downloaded separately in TSV format. Then we have a section with the SNP matrix, the VCF files and also the results of the model selection. Then lastly, we have the resulting phylogenetic tree in the WIC format and this is also represented as a cladrogram with post-app values in the output reports. I have also put a regular representation of the tree on the right side. As you can see, the three samples with identical CGMSD profiles, two of them were clonal and one has a slightly different SNP profile. At the bottom of the report, you can again see the commands that were used to obtain the results. Then as a last step in the workflow, we check the AMR profiles of the samples. In this case, we used a local installation of the pointfile new tool in Galaxy. And as you can see in this example output reports, in one of the samples, we find the mutation in the CATG gene which is associated with resistance to isoniazids. If we then combine all the results of all the different steps, we obtain this final phylogenetic tree along with the sequence types and the resistance profile for all of these examples. If we then combine the results of all the different steps, we obtain this final phylogenetic tree with bootsep values, the sequence type and the AMR resistance profile. Alternatively, we also have several pipelines that perform a complete azure characterization such as the one that I illustrate here for mycobacterium. This is a full overview of all the pipelines that we offer. Some of them are already validated or will be validated soon. These traditions are also described in pre-reviewed publications. And then we also offer a set of tutorials on how to use Galaxy and also for specific tools or pipelines. Then to finish my presentation, I want to acknowledge my colleagues from the BioIT team in SenSano who work really hard to keep our Galaxy instance up to date and running.