What is SCInter?

Here, we have developed a comprehensive Single-Cell transcriptome Integration database for human and mouse, which aims to provide a comprehensive manually curated single cell transcriptome integration database and also supports the provision of gene expression profiles across cell types at sample level. The current version of SCInter includes a total of 115 integrated datasets and 1,016 single-cell samples covering nearly 150 tissues/cell lines. It is worth noting that each sample represents a single-cell expression map confirmed by high-throughput experiments. We identified 12,925 clusters and 8,016,646 cell markers in 457 cell types by using the gene expression profile matrix. At the same time, we have implemented a series of uniform and multiscale identification on each integrated dataset and single cell sample, including accurate cell type annotation, functional gene expressions, data dimension reduction, cell clustering, cell marker, cell differentiation trajectories and etc. In addition, our database already supports scRNA-seq of multiple protocols and platforms, such as 10x Chromium, Microwell-seq, Drop-seq, SMART-seq2 and CEL-Seq2. To sum up, SCInter is a user-friendly database to query, browse and visualize information associated with single cell. We believe that SCInter could become a useful and effective platform for exploring developmental trajectories and heterogeneity of cells in diseases and biological processes.