Abstract Summary Despite the growing availability of sophisticated bioinformatic methods for the analysis of single-cell RNA-seq data, few tools exist that allow biologists without bioinformatic expertise to directly visualize and interact with their own data and results. Here, we present Cerebro ( ce ll re port bro wser), a Shiny- and Electron-based standalone desktop application for macOS and Windows, which allows investigation and inspection of pre-processed single-cell transcriptomics data without requiring bioinformatic experience of the user. Through an interactive and intuitive graphical interface, users can i) explore similarities and heterogeneity between samples and cells clusters in 2D or 3D projections such as t-SNE or UMAP, ii) display the expression level of single genes or genes sets of interest, iii) browse tables of most expressed genes and marker genes for each sample and cluster. We provide a simple example to show how Cerebro can be used and which are its capabilities. Through a focus on flexibility and direct access to data and results, we think Cerebro offers a collaborative framework for bioinformaticians and experimental biologists which facilitates effective interaction to shorten the gap between analysis and interpretation of the data. Availability Cerebro and example data sets are available at https://github.com/romanhaa/Cerebro . Similarly, the R packages cerebroApp and cerebroPrepare R packages are available at https://github.com/romanhaa/cerebroApp and https://github.com/romanhaa/cerebroPrepare , respectively. All components are released under the MIT License.