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.
Please send an e-mail to firstname.lastname@example.org 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.|
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.|