Evidence map›Paper›PMID 18245358›Full record

ArticleGenetics2008

Bayesian variable selection for detecting adaptive genomic differences among populations.

Andrea Riebler, Leonhard Held, Wolfgang Stephan

Abstract read
In one paragraph

Article in Genetics, 2008. 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. Computational Genomics and Its Applications to Anthropological Questions.American journal of biological anthropology · 2024
    Review
  3. Article
  4. Article
  5. Article
  6. Selective Sweeps.Genetics · 2019
    Review
  7. Article
  8. Article
  9. Article
  10. Detection of Selection Signatures on the X Chromosome in Three Sheep Breeds.International journal of molecular sciences · 2015
    Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
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  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

3 authors.

Andrea RieblerInstitute of Social and Preventive Medicine, University of Zurich, Zurich, Switzerland. andrea.riebler@ifspm.uzh.ch
Leonhard Held
Wolfgang Stephan

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We extend an F(st)-based Bayesian hierarchical model, implemented via Markov chain Monte Carlo, for the detection of loci that might be subject to positive selection. This model divides the F(st)-influencing factors into locus-specific effects, population-specific effects, and effects that are specific for the locus in combination with the population. We introduce a Bayesian auxiliary variable for each locus effect to automatically select nonneutral locus effects. As a by-product, the efficiency of the original approach is improved by using a reparameterization of the model. The statistical power of the extended algorithm is assessed with simulated data sets from a Wright-Fisher model with migration. We find that the inclusion of model selection suggests a clear improvement in discrimination as measured by the area under the receiver operating characteristic (ROC) curve. Additionally, we illustrate and discuss the quality of the newly developed method on the basis of an allozyme data set of the fruit fly Drosophila melanogaster and a sequence data set of the wild tomato Solanum chilense. For data sets with small sample sizes, high mutation rates, and/or long sequences, however, methods based on nucleotide statistics should be preferred.

Indexed as

Selection, GeneticAnimalsBayes TheoremComputer SimulationDatabases, GeneticDrosophila melanogasterGenomeModels, GeneticPopulation DynamicsROC CurveSolanum lycopersicum

Identifiers

PMID18245358
PMCPMC2278048

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.