Back to Search Start Over

Vgas: A Viral Genome Annotation System

Authors :
Kai-Yue Zhang
Yi-Zhou Gao
Meng-Ze Du
Shuo Liu
Chuan Dong
Feng-Biao Guo
Source :
Frontiers in Microbiology, Vol 10 (2019)
Publication Year :
2019
Publisher :
Frontiers Media S.A., 2019.

Abstract

The in-depth study of viral genomes is of great help in many aspects, especially in the treatment of human diseases caused by viral infections. With the rapid accumulation of viral sequencing data, improved, or alternative gene-finding systems have become necessary to process and mine these data. In this article, we present Vgas, a system combining an ab initio method and a similarity-based method to automatically find viral genes and perform gene function annotation. Vgas was compared with existing programs, such as Prodigal, GeneMarkS, and Glimmer. Through testing 5,705 virus genomes downloaded from RefSeq, Vgas demonstrated its superiority with the highest average precision and recall (both indexes were 1% higher or more than the other programs); particularly for small virus genomes (≤ 10 kb), it showed significantly improved performance (precision was 6% higher, and recall was 2% higher). Moreover, Vgas presents an annotation module to provide functional information for predicted genes based on BLASTp alignment. This characteristic may be specifically useful in some cases. When combining Vgas with GeneMarkS and Prodigal, better prediction results could be obtained than with each of the three individual programs, suggesting that collaborative prediction using several different software programs is an alternative for gene prediction. Vgas is freely available at http://cefg.uestc.cn/vgas/ or http://121.48.162.133/vgas/. We hope that Vgas could be an alternative virus gene finder to annotate new genomes or reannotate existing genome.

Details

Language :
English
ISSN :
1664302X
Volume :
10
Database :
Directory of Open Access Journals
Journal :
Frontiers in Microbiology
Publication Type :
Academic Journal
Accession number :
edsdoj.145e4b49b04c4e7d9a6962e2d8214e94
Document Type :
article
Full Text :
https://doi.org/10.3389/fmicb.2019.00184