Evidence map›Paper›PMID 40113767›Full record

ArticleNature communications2025

Sparse haplotype-based fine-scale local ancestry inference at scale reveals recent selection on immune responses.

Yaoling Yang, Richard Durbin, Astrid K N Iversen, Daniel J Lawson

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Graph transformer for ancient ancestry inference.bioRxiv : the preprint server for biology · 2026
    Article
  3. Article
  4. Article
  5. An Efficient Dynamic Data Structure for Haplotype Matching and Compression on Biobank-Scale Data.Journal of computational biology : a journal of computational molecular cell biology · 2026
    Article
  6. Article
  7. Article
  8. DynamicbioRxiv : the preprint server for biology · 2025
    Article
  9. Haplotype Matching with GBWT for Pangenome Graphs.bioRxiv : the preprint server for biology · 2025
    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

4 authors.

Yaoling YangDepartment of Statistical Sciences, School of Mathematics, University of Bristol, Bristol, UK. yaoling.yang@bristol.ac.uk.ORCID http://orcid.org/0000-0003-4905-8097
Richard DurbinDepartment of Genetics, University of Cambridge, Cambridge, UK.ORCID http://orcid.org/0000-0002-9130-1006
Astrid K N IversenNuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK.ORCID http://orcid.org/0000-0002-3507-5956
Daniel J LawsonDepartment of Statistical Sciences, School of Mathematics, University of Bristol, Bristol, UK. dan.lawson@bristol.ac.uk.ORCID http://orcid.org/0000-0002-5311-6213

Funding

China Scholarship Council (CSC) 202108060092Oak Foundation OFIL-20-095
6 · The paper itself

Abstract

Increasingly efficient methods for inferring the ancestral origin of genome regions are needed to gain insights into genetic function and history as biobanks grow in scale. Here we describe two near-linear time algorithms to learn ancestry harnessing the strengths of a Positional Burrows-Wheeler Transform. SparsePainter is a faster, sparse replacement of previous model-based 'chromosome painting' algorithms to identify recently shared haplotypes, whilst PBWTpaint uses further approximations to obtain lightning-fast estimation optimized for genome-wide relatedness estimation. The computational efficiency gains of these tools for fine-scale local ancestry inference offer the possibility to analyse large-scale genomic datasets using different approaches. Application to the UK Biobank shows that haplotypes better represent ancestries than principal components, whilst linkage-disequilibrium of ancestry identifies signals of recent changes to population-specific selection for many genomic regions associated with immune responses, suggesting avenues for understanding the pathogen-immune system interplay on a historical timescale.

Indexed as

HaplotypesImmunitySelection, GeneticAlgorithmsGenetics, PopulationGenome, HumanGenome-Wide Association StudyHumansLinkage DisequilibriumPolymorphism, Single Nucleotide

Identifiers

PMID40113767
PMCPMC11926123

What Socratic holds

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LicenceCC BY
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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 Socratic graph.