Profiling differences in microbiome composition regarding a healthy or a disease phenotype is central in microbiome research. It typically involves the sequencing, the data processing, the statistical analysis and the graphical representation of the detected signatures. This process is currently addressed through several separated applications that requires expertise for installation, data processing and in some case, programming skills. We present SHAMAN, which is an interactive web application that facilitates the use of a bioinformatic workflow for metataxonomic analysis, a robust statistical modelling and provides the largest panel of interactive visualizations among current solutions. SHAMAN is specifically designed for biologist for which a unified experience of the different step of the metagenomic analysis could make a difference in term of productivity. It is freely accessible at http://shaman.pasteur.fr/, but also work as a standalone application with docker (aghozlane/shaman), conda and R. The source code is written in R and is available at https://github.com/aghozlane/shaman. Using a mock community sequencing and a published 16S metagenomic dataset, we show here that SHAMAN allows to perform a complete metataxonomic analysis.