CellDepot: A Unified Repository for scRNA-seq Data and Visual Exploration. Issue 11 (15th June 2022) - Lin, Dongdong; Chen, Yirui; Negi, Soumya; Cheng, Derrick; Ouyang, Zhengyu; Sexton, David; Li, Kejie; Zhang, Baohong
Graphical abstract: Highlights: CellDepot contains over 270 processed scRNA-seq datasets from 8 species. CellDepot provides advanced searching and filtering of datasets allowing cross-dataset query of expressed genes. CellDepot integrates with cellxgene VIP, which has more than 20 interactive plotting and analytical modules to cover secondary and tertiary analysis. CellDepot is released as open-source software to motivate crowd contribution, broad adoption, and local deployment for private data. Abstract: CellDepot containing over 270 datasets from 8 species and many tissues serves as an integrated web application to empower scientists in exploring single-cell RNA-seq (scRNA-seq) datasets and comparing the datasets among various studies through a user-friendly interface with advanced visualization and analytical capabilities. To begin with, it provides an efficient data management system that users can upload single cell datasets and query the database by multiple attributes such as species and cell types. In addition, the graphical multi-logic, multi-condition query builder and convenient filtering tool backed by MySQL database system, allows users to quickly find the datasets of interest and compare the expression of gene(s) across these. Moreover, by embedding the cellxgene VIP tool, CellDepot enables fast exploration of individual dataset in the manner of interactivity and scalability to gain more refined insights such as cell composition, gene expression profiles, and differentially expressed genes among cell types by leveraging more than 20 frequently applied plotting functions and high-level analysis methods in single cell research. In summary, the web portal available at http://celldepot.bxgenomics.com, prompts large scale single cell data sharing, facilitates meta-analysis and visualization, and encourages scientists to contribute to the single-cell community in a tractable and collaborative way. Finally, CellDepot is released as open-source software under MIT license to motivate crowd contribution, broad adoption, and local deployment for private datasets.