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Agostinetto G., Sandionigi A., Bruno A., Casiraghi M., Pescini D. (University of Milano-Bicocca, Milan, Italy; Quantia Consulting srl, Milan, Italy)
fimViz is an interactive Python dashboard for the visualization of microbiome patterns and association rules obtained from Association Rule Mining (ARM) approach. ARM is a supervised machine learning procedure able to reconstruct patterns of species and associations between them. ARM can generate numerous patterns and rules that can be evaluated by different parameters (the most used is support, as the frequency of a pattern or a rule in the dataset). Considering the complexity of microbiome data and the wide range of ARM parameters, we developed fimViz as an instrument particularly suited to visualize ARM outputs from microbiome data interactively. fimViz is set so that several parameters can be accepted at the same time, without the user interacting. In particular, users can integrate ARM outputs with metadata (data regarding samples) and taxonomy information. These additional information are then integrated into the dashboard as filters to visualize ARM outputs, dynamically. fimViz includes the common microbiome plots, as heatmaps and ordination plots, guaranteeing a user-friendly instrument to explore patterns and associations in depth.