↓ Skip to main content

PLOS

Viral Quasispecies Assembly via Maximal Clique Enumeration

Overview of attention for article published in PLoS Computational Biology, March 2014
Altmetric Badge

Mentioned by

twitter
5 X users
patent
1 patent
video
1 YouTube creator

Readers on

mendeley
112 Mendeley
citeulike
1 CiteULike
Title
Viral Quasispecies Assembly via Maximal Clique Enumeration
Published in
PLoS Computational Biology, March 2014
DOI 10.1371/journal.pcbi.1003515
Pubmed ID
Authors

Armin Töpfer, Tobias Marschall, Rowena A. Bull, Fabio Luciani, Alexander Schönhuth, Niko Beerenwinkel

Abstract

Virus populations can display high genetic diversity within individual hosts. The intra-host collection of viral haplotypes, called viral quasispecies, is an important determinant of virulence, pathogenesis, and treatment outcome. We present HaploClique, a computational approach to reconstruct the structure of a viral quasispecies from next-generation sequencing data as obtained from bulk sequencing of mixed virus samples. We develop a statistical model for paired-end reads accounting for mutations, insertions, and deletions. Using an iterative maximal clique enumeration approach, read pairs are assembled into haplotypes of increasing length, eventually enabling global haplotype assembly. The performance of our quasispecies assembly method is assessed on simulated data for varying population characteristics and sequencing technology parameters. Owing to its paired-end handling, HaploClique compares favorably to state-of-the-art haplotype inference methods. It can reconstruct error-free full-length haplotypes from low coverage samples and detect large insertions and deletions at low frequencies. We applied HaploClique to sequencing data derived from a clinical hepatitis C virus population of an infected patient and discovered a novel deletion of length 357±167 bp that was validated by two independent long-read sequencing experiments. HaploClique is available at https://github.com/armintoepfer/haploclique. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2-5.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 4%
Netherlands 1 <1%
Belgium 1 <1%
Brazil 1 <1%
Unknown 104 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 23 21%
Researcher 23 21%
Student > Doctoral Student 11 10%
Student > Bachelor 11 10%
Professor > Associate Professor 9 8%
Other 20 18%
Unknown 15 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 38 34%
Biochemistry, Genetics and Molecular Biology 21 19%
Computer Science 19 17%
Immunology and Microbiology 3 3%
Economics, Econometrics and Finance 3 3%
Other 8 7%
Unknown 20 18%