Evidence map›Paper›PMID 19452216›Full record

ReviewMammalian genome : official journal of the International Mammalian Genome Society2009

Next-generation sequencing of vertebrate experimental organisms.

Daniel J Turner, Thomas M Keane, Ian Sudbery, David J Adams

Abstract readReview
In one paragraph

Review in Mammalian genome : official journal of the International Mammalian Genome Society, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing papers in PubMed
–field-weighted citation impact
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

20 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Next-generation sequencing of experimental mouse strains.Mammalian genome : official journal of the International Mammalian Genome Society · 2012
    Review
  8. Article
  9. Article
  10. Review
  11. Review
  12. Sequencing technologies and genome sequencing.Journal of applied genetics · 2011
    Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Article
  18. Review
  19. Next-generation gap.Nature methods · 2009
    Review
  20. Article
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

4 authors.

Daniel J TurnerExperimental Cancer Genetics, Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK.
Thomas M Keane
Ian Sudbery
David J Adams

Funding

Cancer Research UKMedical Research Council G0800024Wellcome Trust
6 · The paper itself

Abstract

Next-generation sequencing technologies are revolutionizing biology by allowing for genome-wide transcription factor binding-site profiling, transcriptome sequencing, and more recently, whole-genome resequencing. While it is currently not possible to generate complete de novo assemblies of higher-vertebrate genomes using next-generation sequencing, improvements in sequence read lengths and throughput, coupled with new assembly algorithms for large data sets, will soon make this a reality. These developments will in turn spawn a revolution in how genomic data are used to understand genetics and how model organisms are used for disease gene discovery. This review provides an overview of the current next-generation sequencing platforms and the newest computational tools for the analysis of next-generation sequencing data. We also describe how next-generation sequencing may be applied in the context of vertebrate model organism genetics.

Indexed as

GenomicsAnimalsHumansSequence Analysis, DNAVertebrates

Identifiers

PMID19452216
PMCPMC2714443

What OpenQuestion holds

Textmetadata
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.