Title |
Identification of Novel Viruses Using VirusHunter -- an Automated Data Analysis Pipeline
|
---|---|
Published in |
PLOS ONE, October 2013
|
DOI | 10.1371/journal.pone.0078470 |
Pubmed ID | |
Authors |
Guoyan Zhao, Siddharth Krishnamurthy, Zhengqiu Cai, Vsevolod L. Popov, Amelia P. Travassos da Rosa, Hilda Guzman, Song Cao, Herbert W. Virgin, Robert B. Tesh, David Wang |
Abstract |
Quick and accurate identification of microbial pathogens is essential for both diagnosis and response to emerging infectious diseases. The advent of next-generation sequencing technology offers an unprecedented platform for rapid sequencing-based identification of novel viruses. We have developed a customized bioinformatics data analysis pipeline, VirusHunter, for the analysis of Roche/454 and other long read Next generation sequencing platform data. To illustrate the utility of VirusHunter, we performed Roche/454 GS FLX titanium sequencing on two unclassified virus isolates from the World Reference Center for Emerging Viruses and Arboviruses (WRCEVA). VirusHunter identified sequences derived from a novel bunyavirus and a novel reovirus in the two samples respectively. Further sequence analysis demonstrated that the viruses were novel members of the Phlebovirus and Orbivirus genera. Both Phlebovirus and Orbivirus genera include many economic important viruses or serious human pathogens. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
India | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 5 | 4% |
United Kingdom | 1 | <1% |
Netherlands | 1 | <1% |
Germany | 1 | <1% |
Unknown | 109 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 25 | 21% |
Student > Ph. D. Student | 24 | 21% |
Student > Master | 20 | 17% |
Other | 9 | 8% |
Student > Bachelor | 9 | 8% |
Other | 16 | 14% |
Unknown | 14 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 53 | 45% |
Biochemistry, Genetics and Molecular Biology | 13 | 11% |
Medicine and Dentistry | 8 | 7% |
Immunology and Microbiology | 7 | 6% |
Computer Science | 6 | 5% |
Other | 11 | 9% |
Unknown | 19 | 16% |