Evidence map›Paper›PMID 29084517›Full record

ReviewBMC biology2017

Detecting positive selection in the genome.

Tom R Booker, Benjamin C Jackson, Peter D Keightley

Abstract readReview
In one paragraph

Review in BMC biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.

0numbers the graph read from it
0cells of the map it votes in
88citing 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

88 citing papers in PubMed.

  1. Article
  2. Article
  3. Evolution of CTCF binding sites in the human genome.Molecular biology and evolution · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
  12. Article
  13. Selection scans and downstream analysis with selscan.Human population genetics and genomics · 2026
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Gene age shapes functional and evolutionary properties of theProceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  19. Selection scans and downstream analysis with selscan.bioRxiv : the preprint server for biology · 2025
    Article
  20. Article

28 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

3 authors.

Tom R BookerInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh, EH9 3FL, UK.
Benjamin C JacksonInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh, EH9 3FL, UK.
Peter D KeightleyInstitute of Evolutionary Biology, University of Edinburgh, Edinburgh, EH9 3FL, UK. peter.keightley@ed.ac.uk.

Funding

Biotechnology and Biological Sciences Research Council
6 · The paper itself

Abstract

Population geneticists have long sought to understand the contribution of natural selection to molecular evolution. A variety of approaches have been proposed that use population genetics theory to quantify the rate and strength of positive selection acting in a species' genome. In this review we discuss methods that use patterns of between-species nucleotide divergence and within-species diversity to estimate positive selection parameters from population genomic data. We also discuss recently proposed methods to detect positive selection from a population's haplotype structure. The application of these tests has resulted in the detection of pervasive adaptive molecular evolution in multiple species.

Indexed as

Evolution, MolecularGenetic VariationGenomeSelection, GeneticGenetics, PopulationHaplotypes

Identifiers

PMID29084517
PMCPMC5662103

What OpenQuestion holds

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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.