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Nucleic Acids Res. 2016 Jan 4;44(D1):D975-9. doi: 10.1093/nar/gkv1314. Epub 2015 Dec 3.

DriverDBv2: a database for human cancer driver gene research.

Author information

1
Institute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan Center for Systems and Synthetic Biology, National Yang-Ming University, Taipei, 11221, Taiwan.
2
Institute of Biomedical Informatics, National Yang-Ming University, Taipei 11221, Taiwan.
3
Research Center for Tumour Medical Science, China Medical University, Taichung, 40402, Taiwan.
4
Department of Genome Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung 80708, Taiwan Center for Infectious Disease and Cancer Research, Kaohsiung Medical University, Kaohsiung 80708, Taiwan.
5
Research Center for Tumour Medical Science, China Medical University, Taichung, 40402, Taiwan Graduate Institute of Cancer Biology, China Medical University, Taichung, 40402, Taiwan.
6
VGH-YM Genomic Research Center, National Yang-Ming University, Taipei 11221, Taiwan Institute of Clinical Medicine, Medical College, National Yang-Ming University, Taipei 11221, Taiwan Institute of Microbiology and Immunology, National Yang-Ming University, Taipei 11221, Taiwan Department of Education and Research, Taipei City Hospital, Taipei 10341, Taiwan hwwang@ym.edu.tw.
7
Research Center for Tumour Medical Science, China Medical University, Taichung, 40402, Taiwan Graduate Institute of Cancer Biology, China Medical University, Taichung, 40402, Taiwan cwc0702@gmail.com.

Abstract

We previously presented DriverDB, a database that incorporates ∼ 6000 cases of exome-seq data, in addition to annotation databases and published bioinformatics algorithms dedicated to driver gene/mutation identification. The database provides two points of view, 'Cancer' and 'Gene', to help researchers visualize the relationships between cancers and driver genes/mutations. In the updated DriverDBv2 database (http://ngs.ym.edu.tw/driverdb) presented herein, we incorporated >9500 cancer-related RNA-seq datasets and >7000 more exome-seq datasets from The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC), and published papers. Seven additional computational algorithms (meaning that the updated database contains 15 in total), which were developed for driver gene identification, are incorporated into our analysis pipeline, and the results are provided in the 'Cancer' section. Furthermore, there are two main new features, 'Expression' and 'Hotspot', in the 'Gene' section. 'Expression' displays two expression profiles of a gene in terms of sample types and mutation types, respectively. 'Hotspot' indicates the hotspot mutation regions of a gene according to the results provided by four bioinformatics tools. A new function, 'Gene Set', allows users to investigate the relationships among mutations, expression levels and clinical data for a set of genes, a specific dataset and clinical features.

PMID:
26635391
PMCID:
PMC4702919
DOI:
10.1093/nar/gkv1314
[Indexed for MEDLINE]
Free PMC Article

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