Among few scRNA-seq data visualization tools evaluated in a recent publication, cellxgene developed by Chan Zuckerberg Initiative is highly recommended because of its scalability and interactivity, which is also adopted by many Human Cell Atlas projects. However, after implemented in house and trained a big community of scientists in our company at Biogen as well as our academic collaborators to use it, quickly we realized it lacks essential visual analytical functions bench scientists are familiar with, such as differential gene expression analysis on all genes, violin, dot, heatmaps, density, multi-panel embedding and volcano plots.
K. Li et al. at Biogen developed an open source web-based interactive tool built upon cellxgene but greatly extended its plotting and analytical capabilities by integrating state-of-the-art tools in this field. It allows users with no programming experience to rapidly explore scRNA-seq data and create high-resolution figures commonly seen in high-profile publications. Furthermore, it is the first tool to the author’s knowledge to allow computational biologists to write their own code to communicate with the hosting server via a mini Jupyter notebook like interface. It opens up unlimited capabilities even beyond the rich set of plotting functions provided in the tool. We believe this work could add valuable scientific contribution back to the single cell community, and it could entice contributions from other developers through the elegant yet simple plugin design.
The demo of tool is hosted at https://cellxgenevip-ms.bxgenomics.com and its source code is also provided at https://github.com/interactivereport/cellxgene_VIP for local installation.