DriverDB: An exome sequencing database for cancer driver gene identification

Wei Chung Cheng, I. Fang Chung, Chen Yang Chen, Hsing Jen Sun, Jun Jeng Fen, Wei Chun Tang, Ting Yu Chang, Tai Tong Wong*, Hsei Wei Wang

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

66 Scopus citations


Exome sequencing (exome-seq) has aided in the discovery of a huge amount of mutations in cancers, yet challenges remain in converting oncogenomics data into information that is interpretable and accessible for clinical care. We constructed DriverDB (, a database which incorporates 6079 cases of exome-seq data, annotation databases (such as dbSNP, 1000 Genome and Cosmic) and published bioinformatics algorithms dedicated to driver gene/mutation identification. We provide two points of view, 'Cancer' and 'Gene', to help researchers to visualize the relationships between cancers and driver genes/mutations. The 'Cancer' section summarizes the calculated results of driver genes by eight computational methods for a specific cancer type/dataset and provides three levels of biological interpretation for realization of the relationships between driver genes. The 'Gene' section is designed to visualize the mutation information of a driver gene in five different aspects. Moreover, a 'Meta-Analysis' function is provided so researchers may identify driver genes in customer-defined samples. The novel driver genes/mutations identified hold potential for both basic research and biotech applications.

Original languageEnglish
Pages (from-to)D1048-D1054
JournalNucleic acids research
Issue numberD1
StatePublished - 1 Jan 2014


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