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http://dx.doi.org/10.5808/GI.2020.18.1.e5

PAIVS: prediction of avian influenza virus subtype  

Park, Hyeon-Chun (Department of Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea)
Shin, Juyoun (Department of Microbiology, College of Medicine, The Catholic University of Korea)
Cho, Sung-Min (Integrated Research Center for Genome Polymorphism, College of Medicine, The Catholic University of Korea)
Kang, Shinseok (Chungbuk Veterinary Service Laboratory)
Chung, Yeun-Jun (Department of Microbiology, College of Medicine, The Catholic University of Korea)
Jung, Seung-Hyun (Cancer Evolution Research Center, College of Medicine, The Catholic University of Korea)
Abstract
Highly pathogenic avian influenza (HPAI) viruses have caused severe respiratory disease and death in poultry and human beings. Although most of the avian influenza viruses (AIVs) are of low pathogenicity and cause mild infections in birds, some subtypes including hemagglutinin H5 and H7 subtype cause HPAI. Therefore, sensitive and accurate subtyping of AIV is important to prepare and prevent for the spread of HPAI. Next-generation sequencing (NGS) can analyze the full-length sequence information of entire AIV genome at once, so this technology is becoming a more common in detecting AIVs and predicting subtypes. However, an analysis pipeline of NGS-based AIV sequencing data, including AIV subtyping, has not yet been established. Here, in order to support the pre-processing of NGS data and its interpretation, we developed a user-friendly tool, named prediction of avian influenza virus subtype (PAIVS). PAIVS has multiple functions that support the pre-processing of NGS data, reference-guided AIV subtyping, de novo assembly, variant calling and identifying the closest full-length sequences by BLAST, and provide the graphical summary to the end users.
Keywords
AIV subtypes; avian influenza virus; next-generation sequencing; viral genome;
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