DocumentCode
191043
Title
VGA: A method for viral quasispecies assembly from ultra-deep sequencing data
Author
Mangul, Serghei ; Wu, Nicholas C. ; Mancuso, Nicholas ; Zelikovsky, Alexander ; Ren Sun ; Eskin, Eleazar
Author_Institution
Comput. Sci. Dept., Univ. of California, Los Angeles, Los Angeles, CA, USA
fYear
2014
fDate
2-4 June 2014
Firstpage
1
Lastpage
1
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
diseases; genomics; medical computing; microorganisms; HIV viral quasispecies; VGA; Viral Genome Assembler; high-fidelity sequencing protocol; individual barcodes; rare quasispecies; real datasets; sequencing errors; sequencing fragments; synthetic datasets; ultradeep sequencing data; viral assembly method; viral quasispecies assembly; Assembly; Computer science; Human immunodeficiency virus; Protocols; Sequential analysis; Sociology; Statistics; NGS; error-correction protocol; viral assembly; viral quasispecies;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Advances in Bio and Medical Sciences (ICCABS), 2014 IEEE 4th International Conference on
Conference_Location
Miami, FL
Print_ISBN
978-1-4799-5786-6
Type
conf
DOI
10.1109/ICCABS.2014.6863932
Filename
6863932
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