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DriverDBv2: a database for human cancer driver gene research
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 researche...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702919/ https://www.ncbi.nlm.nih.gov/pubmed/26635391 http://dx.doi.org/10.1093/nar/gkv1314 |
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author | Chung, I-Fang Chen, Chen-Yang Su, Shih-Chieh Li, Chia-Yang Wu, Kou-Juey Wang, Hsei-Wei Cheng, Wei-Chung |
author_facet | Chung, I-Fang Chen, Chen-Yang Su, Shih-Chieh Li, Chia-Yang Wu, Kou-Juey Wang, Hsei-Wei Cheng, Wei-Chung |
author_sort | Chung, I-Fang |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-4702919 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-47029192016-01-07 DriverDBv2: a database for human cancer driver gene research Chung, I-Fang Chen, Chen-Yang Su, Shih-Chieh Li, Chia-Yang Wu, Kou-Juey Wang, Hsei-Wei Cheng, Wei-Chung Nucleic Acids Res Database Issue 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. Oxford University Press 2016-01-04 2015-12-03 /pmc/articles/PMC4702919/ /pubmed/26635391 http://dx.doi.org/10.1093/nar/gkv1314 Text en © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Database Issue Chung, I-Fang Chen, Chen-Yang Su, Shih-Chieh Li, Chia-Yang Wu, Kou-Juey Wang, Hsei-Wei Cheng, Wei-Chung DriverDBv2: a database for human cancer driver gene research |
title | DriverDBv2: a database for human cancer driver gene research |
title_full | DriverDBv2: a database for human cancer driver gene research |
title_fullStr | DriverDBv2: a database for human cancer driver gene research |
title_full_unstemmed | DriverDBv2: a database for human cancer driver gene research |
title_short | DriverDBv2: a database for human cancer driver gene research |
title_sort | driverdbv2: a database for human cancer driver gene research |
topic | Database Issue |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4702919/ https://www.ncbi.nlm.nih.gov/pubmed/26635391 http://dx.doi.org/10.1093/nar/gkv1314 |
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