Database Commons

a catalog of biological databases

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

Database Profile


General information

Full name: Coronavirus GenBrowser
Description: Coronavirus GenBrowser (CGB), based on a highly efficient analysis framework and a node-picking rendering strategy, enables easy analysis and visualization of SARS-CoV-2 genomic sequences with the transmission-related metadata.
Year founded: 2021
Last update:
Real time : Checking...
Country/Region: China

Classification and Labelling

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Contact information

University/Institution: Beijing Institute of Genomics, Chinese Academy of Sciences
Address: No.1 Beichen West Road, Chaoyang District
City: Beijingni
Province/State: Beijing
Country/Region: China
Contact name (PI/Team): Wenming Zhao
Contact email (PI/Helpdesk):


Coronavirus GenBrowser for monitoring the transmission and evolution of SARS-CoV-2. [PMID: 35043153]
Yu D, Yang X, Tang B, Pan YH, Yang J, Duan G, Zhu J, Hao ZQ, Mu H, Dai L, Hu W, Zhang M, Cui Y, Jin T, Li CP, Ma L, Language translation team, Su X, Zhang G, Zhao W, Li H.

Genomic epidemiology is important to study the COVID-19 pandemic, and more than two million severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic sequences were deposited into public databases. However, the exponential increase of sequences invokes unprecedented bioinformatic challenges. Here, we present the Coronavirus GenBrowser (CGB) based on a highly efficient analysis framework and a node-picking rendering strategy. In total, 1,002,739 high-quality genomic sequences with the transmission-related metadata were analyzed and visualized. The size of the core data file is only 12.20 MB, highly efficient for clean data sharing. Quick visualization modules and rich interactive operations are provided to explore the annotated SARS-CoV-2 evolutionary tree. CGB binary nomenclature is proposed to name each internal lineage. The pre-analyzed data can be filtered out according to the user-defined criteria to explore the transmission of SARS-CoV-2. Different evolutionary analyses can also be easily performed, such as the detection of accelerated evolution and ongoing positive selection. Moreover, the 75 genomic spots conserved in SARS-CoV-2 but non-conserved in other coronaviruses were identified, which may indicate the functional elements specifically important for SARS-CoV-2. The CGB was written in Java and JavaScript. It not only enables users who have no programming skills to analyze millions of genomic sequences, but also offers a panoramic vision of the transmission and evolution of SARS-CoV-2.

Brief Bioinform. 2022:23(2) | 0 Citations (from Europe PMC, 2022-05-15)



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Record metadata

Created on: 2022-01-26
Curated by:
Lina Ma [2022-05-15]
Zhang Sisi [2022-01-27]
Dong Zou [2022-01-26]
Zhang Sisi [2022-01-26]