CVCDAP stands for Cancer Virtual Cohort Discovery Analysis Platform. It is an open-access data portal of a large variety of cancer multi-omics data including public data and in-house data. The CVCDAP provides convenient data analysis and visualization tools for user-defined cohorts, to allow quick data mining to reproduce published results and identify new hypothesis.


The CVCDAP was developed by Meng Cai, Xiaoqing Guan and Yang Du at the Center for Cancer Bioinformatics, headed by Dr.  Jianmin Wu

Please send an e-mail to caimeng@bjmu.edu.cn for questions and suggestions.


The pan-cancer datasets from https://gdc.cancer.gov/about-data/publications/pancanatlas are used in the CVCDAP database.

These R packages (maftools, limma, pheatmap, survminer, gsea) are used in the CVCDAP analysis tools.

EnhancedVolcano Kevin Blighe (2019). EnhancedVolcano: Publication-ready volcano plots with enhanced colouring and labeling. R package version 1.0.1. https://github.com/kevinblighe/EnhancedVolcano
GSEA Subramanian, A., et al., Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A, 2005. 102(43): p. 15545-50.
limma Ritchie, M.E., et al., limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic Acids Res, 2015. 43(7): p. e47.

Mootha, V.K., et al., PGC-1alpha-responsive genes involved in oxidative phosphorylation are coordinately downregulated in human diabetes. Nat Genet, 2003. 34(3): p. 267-73.

maftools Mayakonda, A., et al., Maftools: efficient and comprehensive analysis of somatic variants in cancer. Genome Res, 2018. 28(11): p. 1747-1756.