Huang, C.; Liu, Z.; Guo, Y.; Wang, W.; Yuan, Z.; Guan, Y.; Pan, D.; Hu, Z.; Sun, L.; Fu, Z.; Bian, S.

Single-cell multi-omics data is a valuable resource to promote the understanding of cancer. However, multimodal data analysis is challenging for most cancer researchers, and there is still a lack of online databases that can bridge the gap. Here we introduced scCancerExplorer, which is a user-friendly database designed for exploring single-cell multi-omics data of human pan-cancer. We processed more than 110 datasets covering single-cell multiomics data from 51 human cancer types, and provides 5 major modules and 12 useful functions for conveniently exploring those data. (1) The \"Integrated multi-omics analysis\" module enables users explore a gene from multimodal perspectives, such as the gene expression levels, survival analysis, transcription factor activity, and the DNA methylation levels of promoter regions. (2) With single-cell transcriptome module, users can explore the integrated pan-cancer datasets, compare the expression profiles between primary tumor and metastases, and generate customized figures. (3) With single-cell epigenome module, users can explore promoter DNA methylation levels in both normal and cancer cells, DNA methylation state at single CpG resolution, and chromatin accessibility patterns of different cell types. (4) For single-cell genome data, users can visualize the copy number variations of cancer cells for each patient. (5) Moreover, TCGA survival analysis can be performed conveniently. Users can not only group the patients according to gene expression levels, but also select patients by gene mutation states, pathological subtypes, and cancer stages. In summary, scCancerExplorer is a powerful database for convenient data mining by simple clicking, and gaining novel insights into human pan-cancer. scCancerExplorer is freely accessible at https://bianlab.cn/scCancerExplorer.