Evidence map›Paper›PMID 39227130›Full record

ReviewAnnual review of genetics2024

Population Genomic Scans for Natural Selection and Demography.

Xiaoheng Cheng, Matthias Steinrücken

Abstract readReview
In one paragraph

Review in Annual review of genetics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. 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

2 authors.

Xiaoheng ChengDepartment of Ecology and Evolution, University of Chicago, Chicago, Illinois, USA; email: steinrue@uchicago.edu.
Matthias SteinrückenDepartment of Human Genetics, University of Chicago, Chicago, Illinois, USA.

Funding

Population genetic methods to detect population structure and adaptation using modern and ancient genomic datasetsR01GM146051 · NIGMS · UNIVERSITY OF CHICAGO · PI Matthias Steinruecken · 2022 to 2026
$1.7M
NIGMS NIH HHS R01 GM146051
6 · The paper itself

Abstract

Uncovering the fundamental processes that shape genomic variation in natural populations is a primary objective of population genetics. These processes include demographic effects such as past changes in effective population size or gene flow between structured populations. Furthermore, genomic variation is affected by selection on nonneutral genetic variants, for example, through the adaptation of beneficial alleles or balancing selection that maintains genetic variation. In this article, we discuss the characterization of these processes using population genetic models, and we review methods developed on the basis of these models to unravel the underlying processes from modern population genomic data sets. We briefly discuss the conditions in which these approaches can be used to infer demography or identify specific nonneutral genetic variants and cases in which caution is warranted. Moreover, we summarize the challenges of jointly inferring demography and selective processes that affect neutral variation genome-wide.

Indexed as

Genetics, PopulationGenetic VariationModels, GeneticSelection, GeneticAnimalsDemographyGene FlowGenomicsHumansdemographic historygenomic variationnatural selectionpopulation genetics

Identifiers

PMID39227130
PMCPMC12914728

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.