TY - JOUR
T1 - DriverDBv2
T2 - A database for human cancer driver gene research
AU - Chung, I. Fang
AU - Chen, Chen Yang
AU - Su, Shih Chieh
AU - Li, Chia Yang
AU - Wu, Kou Juey
AU - Wang, Hsei Wei
AU - Cheng, Wei Chung
N1 - Publisher Copyright:
© The Author(s) 2015.
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=84976876714&partnerID=8YFLogxK
U2 - 10.1093/nar/gkv1314
DO - 10.1093/nar/gkv1314
M3 - Article
C2 - 26635391
AN - SCOPUS:84976876714
SN - 0305-1048
VL - 44
SP - D975-D979
JO - Nucleic acids research
JF - Nucleic acids research
IS - D1
ER -