Reconstruction of influenza a virus variants from PacBio reads

Author

Artyomenko, Alexander ; Mangul, Serghei ; Wu, Nicholas C. ; Eskin, Eleazar ; Ren Sun ; Zelikovsky, Alexander

Author_Institution

Dept. of Comput. Sci., Georgia State Univ., Atlanta, GA, USA

fYear

2014

fDate

2-4 June 2014

Firstpage

1

Lastpage

1

Abstract

Pacific Biosciences (PacBio) sequencing is providing thousands of reads with the length up to 10,000 bases. In most cases this length is enough to cover entire region of interest however this technology has high (≈ 15%) error rate. We propose a method for viral haplotype reconstruction generalizes k-means clustering with Hamming distance and capable of handling up to 25% random errors. When applied to PacBio reads from an Influenza A Virus (IAV) sample with ten variants, our method was able to reconstruct the four most frequent.

Keywords

bioinformatics; diseases; error handling; genomics; microorganisms; pattern clustering; Hamming distance; IAV; Influenza A Virus sample; PacBio reads; Pacific Biosciences sequencing; error rate; influenza reconstruction; k-means clustering; random error handling; viral haplotype reconstruction; virus variants; Biology; Cloning; Educational institutions; Hamming distance; Sequential analysis; Sociology; Statistics; PacBio; clustering; 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.2014.6863935

Filename

6863935