Evidence map›Paper›PMID 18437230›Full record

ArticlePLoS computational biology2008

Viral population estimation using pyrosequencing.

Nicholas Eriksson, Lior Pachter, Yumi Mitsuya, Soo-Yon Rhee, Chunlin Wang, Baback Gharizadeh, Mostafa Ronaghi, Robert W Shafer, Niko Beerenwinkel

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 papers.

0numbers the graph read from it
0cells of the map it votes in
114citing papers in PubMed
15.2field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

114 citing papers in PubMed, 223 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Haploflow: Strain-resolvedbioRxiv : the preprint server for biology · 2021
    Article
  6. Review
  7. Review
  8. Article
  9. Article
  10. Article
  11. Evaluation of haplotype callers for next-generation sequencing of viruses.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2020
    Article
  12. Genomic characterization of hepatitis C virus transmitted founder variants with deep sequencing.Infection, genetics and evolution : journal of molecular epidemiology and evolutionary genetics in infectious diseases · 2019
    Article
  13. Article
  14. Review
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Generic Amplicon Deep Sequencing to DetermineFrontiers in microbiology · 2017
    Article

54 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 5 institutions in 2 countries.

Nicholas ErikssonDepartment of Statistics, University of Chicago, Chicago, Illinois, United States of America. eriksson@galton.uchicago.edu
Lior Pachter
Yumi Mitsuya
Soo-Yon Rhee
Chunlin Wang
Baback Gharizadeh
Mostafa Ronaghi
Robert W Shafer
Niko Beerenwinkel
Stanford Medicine · USStanford University · USETH Zurich · CHUniversity of California, Berkeley · USUniversity of Chicago · US

Funding

Hepatitis C Virus Quasispecies in the Resistance to Antiviral TherapyR01DK080711 · NIDDK · SAINT LOUIS UNIVERSITY · PI FAN, XIAOFENG · 2008 to 2012
$1.5M
NIDDK NIH HHS R01 DK080711
6 · The paper itself

Abstract

The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate-based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug-resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an expectation-maximization (EM) algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.

Indexed as

AlgorithmsBase SequenceChromosome MappingDNA, ViralGenetic VariationHIVMolecular Sequence DataSequence AlignmentSequence Analysis, DNADNA, Viral

Identifiers

PMID18437230
PMCPMC2323617
OpenAlexW2170765088

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.