Unsupervised deconvolution algorithms are often used to estimate cell composition from bulk tissue samples. However, applying cell type deconvolution and interpreting the results remains a challenge, even more without prior training in bioinformatics. We propose here a tool for estimating and identifying cell type composition from bulk transcriptomes or methylomes. DECOMICS is a shiny-web application dedicated to unsupervised deconvolution approaches of bulk omic data. It provides (i) a variety of existing algorithms to perform deconvolution on the gene expression or methylation-level matrix, (ii) an enrichment analysis module to aid biological interpretation of the deconvolved components, based on enrichment analysis, and (iii) some visualisation tools. Input data can be downloaded in csv format and pre-processed in the web application (normalisation, transformation and feature selection). The results of the deconvolution, enrichment and visualisation processes can be downloaded. Availability and implementation: DECOMICS is an R-shiny web application that can be launched (i) directly from a local R session using the R package available here: https://gitlab.in2p3.fr/Magali.Richard/decomics (either by installing it locally or via a virtual machine and a Docker image that we provide); or (ii) in the Biosphere-IFB Clouds Federation for Life Science, a multi-cloud environment scalable for high-performance computing: https://biosphere.france-bioinformatique.fr/catalogue/appliance/193/.