1. cellxgene https://github.com/chanzuckerberg/cellxgene
2. cellar https://github.com/euxhenh/cellar
3. scSVA: an interactive tool for big data visualization and exploration in single-cell omics https://www.biorxiv.org/content/10.1101/512582v1
4. ASAP: a web-based platform for the analysis and interactive visualization of single-cell RNA-seq data https://academic.oup.com/bioinformatics/article/33/19/3123/3852081?login=false
5. [iSEE](https://bioconductor.org/packages/release/bioc/html/iSEE.html) Provides functions for creating an interactive Shiny-based graphical user interface for exploring data stored in SummarizedExperiment objects, including row- and column-level metadata
6. [VISION](https://github.com/YosefLab/VISION) A high-throughput and unbiased module for interpreting scRNA-seq data.
7. [DISCO](http://immunesinglecell.org/): Deep Integration of Single-Cell Omics. Want to visual millions of cell online and annotate cell type automatically? Try it!!! Make single cell easier and make life easier!
8. [TISCH](http://tisch.comp-genomics.org/) Tumor Immune Single-cell Hub (TISCH) is a scRNA-seq database focusing on tumor microenvironment (TME).
9. [CancerSCEM](https://ngdc.cncb.ac.cn/cancerscem) To date, CancerSCE version 1.0 consists of 208 cancer samples across 28 studies and 20 human cancer types
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