scHLens: a web server for hierarchically and interactively exploring single cell RNA-seq data.

Abstract

With the great advancement of single-cell transcriptome technologies, the identification of cellular heterogeneity from scRNA-seq data has become an important task in biomedical research. There are several challenges associated with the existing analysis methods: (i) The reliance on command-line interfaces creates a substantial technical barrier for researchers lacking computational expertise; (ii) existing methods or platforms usually lack flexibility in workflow customization, forcing users into rigid analytical pipelines; (iii) hierarchical cellular subtypes challenge conventional clustering, as fixed-resolution analyses prevent the detection of biologically subtype cells. Here, we develop a hierarchical and interactive web server named scHLens. scHLens supports a user-defined analysis pipeline and hierarchical exploration mode, providing various visualization views and interaction operations. The three case studies demonstrate scHLens's ability to identify cellular heterogeneity. The online web server version is freely available at http://schlens.csuligroup.com, while the Docker version is available at https://hub.docker.com/r/zhiweideng975/schlens, and the source code can be obtained at https://github.com/ZhiweiDeng459/scHLens.