Evidence map›Paper›PMID 30459280›Full record

ArticleGenetics2019

Local PCA Shows How the Effect of Population Structure Differs Along the Genome.

Han Li, Peter Ralph

Open access · bronzeAbstract read
In one paragraph

Article in Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 117 papers.

0numbers the graph read from it
0cells of the map it votes in
117citing papers in PubMed
11.6field-weighted citation impact, top 1% of its field
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

117 citing papers in PubMed, 243 citations in OpenAlex.

  1. Article
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  3. Inversion characterization inbioRxiv : the preprint server for biology · 2026
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57 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

2 authors at 2 institutions in 1 country.

Han LiDepartment of Molecular and Computational Biology, University of Southern California, Los Angeles, California 90089.
Peter RalphDepartment of Molecular and Computational Biology, University of Southern California, Los Angeles, California 90089 plr@uoregon.edu.ORCID 0000-0002-9459-6866
University of Oregon · USUniversity of Southern California · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Population structure leads to systematic patterns in measures of mean relatedness between individuals in large genomic data sets, which are often discovered and visualized using dimension reduction techniques such as principal component analysis (PCA). Mean relatedness is an average of the relationships across locus-specific genealogical trees, which can be strongly affected on intermediate genomic scales by linked selection and other factors. We show how to use local PCA to describe this intermediate-scale heterogeneity in patterns of relatedness, and apply the method to genomic data from three species, finding in each that the effect of population structure can vary substantially across only a few megabases. In a global human data set, localized heterogeneity is likely explained by polymorphic chromosomal inversions. In a range-wide data set of

Indexed as

Genetic VariationGenome, HumanGenome, InsectGenome, PlantModels, GeneticAnimalsEvolution, MolecularGene FrequencyHumansPrincipal Component AnalysisSelection, Geneticgenomic landscapelocal PCApopulation structurevisualization

Identifiers

PMID30459280
PMCPMC6325702
OpenAlexW2952801562

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.