@inproceedings{ed1a666b398f4ce28c41605b25c8f6dd,
title = "VGA: A method for viral quasispecies assembly from ultra-deep sequencing data",
abstract = "We present VGA, an accurate method for viral quasispecies assembly from ultra-deep sequencing data. The proposed method consists of a high-fidelity sequencing protocol and an accurate method for viral quasispecies assembly, referred to as Viral Genome Assembler (VGA). The proposed protocol is able to eliminate sequencing errors by using individual barcodes attached to the sequencing fragments. Results on both synthetic and real datasets show that our method able to accurately assemble HIV viral quasispecies and detect rare quasispecies previously undetectable due to sequencing errors. VGA outperforms state-of-the-art methods for the viral assembly. Furthermore, our method is the first viral assembly method which scales to millions of sequencing reads. Our tool VGA is freely available at http://genetics.cs.ucla.edu/vga/.",
keywords = "NGS, error-correction protocol, viral assembly, viral quasispecies",
author = "Serghei Mangul and Wu, {Nicholas C.} and Nicholas Mancuso and Alex Zelikovsky and Ren Sun and Eleazar Eskin",
note = "Publisher Copyright: {\textcopyright} 2014 IEEE.; 2014 IEEE 4th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2014 ; Conference date: 02-06-2014 Through 04-06-2014",
year = "2014",
month = jul,
day = "24",
doi = "10.1109/ICCABS.2014.6863932",
language = "English (US)",
series = "2014 IEEE 4th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2014 IEEE 4th International Conference on Computational Advances in Bio and Medical Sciences, ICCABS 2014",
address = "United States",
}
