QUENTIN: reconstruction of disease transmissions from viral quasispecies genomic data
Author(s) -
Pavel Skums,
Alex Zelikovsky,
Rahul Singh,
Walker Gussler,
Zoya Dimitrova,
Sergey Knyazev,
Igor Mandric,
Sumathi Ramachandran,
David S. Campo,
Deeptanshu Jha,
Leonid Bunimovich,
Elizabeth Costenbader,
Connie J. Sexton,
Siobhán O’Connor,
Guoliang Xia,
Yury Khudyakov
Publication year - 2017
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/btx402
Subject(s) - viral quasispecies , inference , transmission (telecommunications) , viral evolution , computational biology , biology , host (biology) , genomics , computer science , virology , genetics , genome , virus , artificial intelligence , hepatitis c virus , gene , telecommunications
Genomic analysis has become one of the major tools for disease outbreak investigations. However, existing computational frameworks for inference of transmission history from viral genomic data often do not consider intra-host diversity of pathogens and heavily rely on additional epidemiological data, such as sampling times and exposure intervals. This impedes genomic analysis of outbreaks of highly mutable viruses associated with chronic infections, such as human immunodeficiency virus and hepatitis C virus, whose transmissions are often carried out through minor intra-host variants, while the additional epidemiological information often is either unavailable or has a limited use.
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