Evidence map›Paper›PMID 19204373›Full record

ArticleGenetics2009

Detecting selective sweeps: a new approach based on hidden markov models.

Simon Boitard, Christian Schlötterer, Andreas Futschik

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in Genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed, 1 pooled it
–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

28 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
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  4. Review
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  7. Article
  8. Article
  9. Genomic divergence and adaptive convergence inProceedings of the National Academy of Sciences of the United States of America · 2019
    Article
  10. Article
  11. Selective Sweeps.Genetics · 2019
    Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
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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

3 authors.

Simon BoitardInstitute of Statistics and Decision Support Systems, University of Vienna, Vienna, Austria. simon.boitard@toulouse.inra.fr
Christian Schlötterer
Andreas Futschik

Funding

Austrian Science Fund FWF P 19467
6 · The paper itself

Abstract

Detecting and localizing selective sweeps on the basis of SNP data has recently received considerable attention. Here we introduce the use of hidden Markov models (HMMs) for the detection of selective sweeps in DNA sequences. Like previously published methods, our HMMs use the site frequency spectrum, and the spatial pattern of diversity along the sequence, to identify selection. In contrast to earlier approaches, our HMMs explicitly model the correlation structure between linked sites. The detection power of our methods, and their accuracy for estimating the selected site location, is similar to that of competing methods for constant size populations. In the case of population bottlenecks, however, our methods frequently showed fewer false positives.

Indexed as

Markov ChainsModels, GeneticSelection, GeneticAlgorithmsComputer SimulationDemographyEvolution, MolecularGenetics, PopulationGenetic VariationGenomic InstabilityHumansSequence Alignment

Identifiers

PMID19204373
PMCPMC2666521

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.