Next generation sequencing (NGS) has become the norm of cancer genomic researches. Large-scale cancer sequencing projects seek to comprehensively uncover mutated genes that confer a selective advantage for cancer cells. Numerous computational algorithms have been developed to find genes that drive cancer based on their patterns of mutation in a patient cohort. It has been noted that the distinct features of driver gene alterations in different subgroups are based on clinical characteristics. Previously, we have developed a database, DriverDB, to integrate all public cancer sequencing data and to identify cancer driver genes according to bioinformatics tools. In this chapter, we describe the use of the function "Meta-Analysis" in DriverDB that offers a list of clinical characteristics to define samples and provides a high degree of freedom for researchers to utilize the huge amounts of sequencing data. Moreover, researchers can use the "Gene" section to explore a single driver gene in all cancers by different kinds of aspects after identifying the specific driver genes by "Meta-Analysis." DriverDB is available at http://ngs.ym.edu.tw/driverdb/ .
Keywords: Cancer; Driver genes; Mutations; Next generation sequencing; Subgroups.