Database Commons

a catalog of biological databases

e.g., animal; RNA; Methylation; China

Database Profile

General information

URL: https://oncovar.org/
Full name: An integrated database and analysis platform for oncogenic driver variants in cancers
Description: The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, ‘Mutation’, ‘Gene’, ‘Pathway’ and ‘Cancer’, to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.
Year founded: 2019
Last update: 2020
Version: V1
Accessibility:
Manual:
Accessible
Real time : Checking...
Country/Region: China
Data type:
DNA
Data object:
Database category:
Major organism:
Keywords:

Contact information

University/Institution: Peking University
Address:
City: Beijing
Province/State: Beijing
Country/Region: China
Contact name (PI/Team): Fengbiao Mao
Contact email (PI/Helpdesk): maofengbiao@126.com

Publications

33179738
OncoVar: an integrated database and analysis platform for oncogenic driver variants in cancers. [PMID: 33179738]
Wang T, Ruan S, Zhao X, Shi X, Teng H, Zhong J, You M, Xia K, Sun Z, Mao F.

The prevalence of neutral mutations in cancer cell population impedes the distinguishing of cancer-causing driver mutations from passenger mutations. To systematically prioritize the oncogenic ability of somatic mutations and cancer genes, we constructed a useful platform, OncoVar (https://oncovar.org/), which employed published bioinformatics algorithms and incorporated known driver events to identify driver mutations and driver genes. We identified 20 162 cancer driver mutations, 814 driver genes and 2360 pathogenic pathways with high-confidence by reanalyzing 10 769 exomes from 33 cancer types in The Cancer Genome Atlas (TCGA) and 1942 genomes from 18 cancer types in International Cancer Genome Consortium (ICGC). OncoVar provides four points of view, 'Mutation', 'Gene', 'Pathway' and 'Cancer', to help researchers to visualize the relationships between cancers and driver variants. Importantly, identification of actionable driver alterations provides promising druggable targets and repurposing opportunities of combinational therapies. OncoVar provides a user-friendly interface for browsing, searching and downloading somatic driver mutations, driver genes and pathogenic pathways in various cancer types. This platform will facilitate the identification of cancer drivers across individual cancer cohorts and helps to rank mutations or genes for better decision-making among clinical oncologists, cancer researchers and the broad scientific community interested in cancer precision medicine.

Nucleic Acids Res. 2021:49(D1) | 3 Citations (from Europe PMC, 2021-05-01)

Ranking

All databases:
2133/5030 (57.614%)
Genotype phenotype and variation:
308/702 (56.268%)
Health and medicine:
427/1056 (59.659%)
2133
Total Rank
3
Citations
3
z-index

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Record metadata

Created on: 2021-02-05
Curated by:
lin liu [2021-03-10]
Fengbiao Mao [2021-02-05]