Evidence map›Paper›PMID 32533945›Full record

ArticleAmerican journal of human genetics2020

Population-Specific Recombination Maps from Segments of Identity by Descent.

Ying Zhou, Brian L Browning, Sharon R Browning

Open access · bronzeAbstract read
In one paragraph

Article in American journal of human genetics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.3field-weighted citation impact, top 5% 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

28 citing papers in PubMed, 38 citations in OpenAlex.

  1. Review
  2. Article
  3. Estimating recombination fraction via Pearson correlation.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2026
    Article
  4. Article
  5. Identity-by-descent segments in large samples.Theoretical population biology · 2025
    Article
  6. Article
  7. Fast simulation of identity-by-descent segments.Bulletin of mathematical biology · 2025
    Article
  8. Review
  9. Fast simulation of identity-by-descent segments.bioRxiv : the preprint server for biology · 2025
    Article
  10. Article
  11. HLA Genetics for the Human Diseases.Advances in experimental medicine and biology · 2024
    Review
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Review
  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 at 2 institutions in 1 country.

Ying ZhouDepartment of Biostatistics, University of Washington, Seattle, WA 98195, USA. Electronic address: yz001@uw.edu.
Brian L BrowningDivision of Medical Genetics, Department of Medicine, University of Washington, Seattle, WA 98195, USA.
Sharon R BrowningDepartment of Biostatistics, University of Washington, Seattle, WA 98195, USA. Electronic address: sguy@uw.edu.
University of Washington · USUniversity of Washington Medical Center · US

Funding

Studies of Rare Genetic Variation in the Isolated Population of SardiniaR01HL117626 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI ABECASIS, GONCALO · 2013 to 2016
$10.5M
Rare variants and NHLBI traits in deeply phenotyped cohortsR01HL120393 · NHLBI · UNIVERSITY OF WASHINGTON · PI PSATY, BRUCE M, RICE, KENNETH M. · 2014 to 2016
$8.9M
Improved gene mapping for whole genome dataR01HG005701 · NHGRI · UNIVERSITY OF WASHINGTON · PI BROWNING, BRIAN LEE · 2010 to 2024
$4.4M
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
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NHGRI NIH HHS R01 HG005701NHLBI NIH HHS HHSN268201100037CNHLBI NIH HHS HHSN268201500001CNHLBI NIH HHS HHSN268201500001INHLBI NIH HHS HHSN268201500014CNHLBI NIH HHS HHSN268201800010INHLBI NIH HHS HHSN268201800011CNHLBI NIH HHS HHSN268201800011INHLBI NIH HHS HHSN268201800012CNHLBI NIH HHS HHSN268201800012INHLBI NIH HHS HHSN268201800014CNHLBI NIH HHS HHSN268201800014INHLBI NIH HHS HHSN268201800015INHLBI NIH HHS N01 HC025195NHLBI NIH HHS R01 HL117626NHLBI NIH HHS R01 HL120393NIMHD NIH HHS HHSN268201800013I
6 · The paper itself

Abstract

Recombination rates vary significantly across the genome, and estimates of recombination rates are needed for downstream analyses such as haplotype phasing and genotype imputation. Existing methods for recombination rate estimation are limited by insufficient amounts of informative genetic data or by high computational cost. We present a method and software, called IBDrecomb, for using segments of identity by descent to infer recombination rates. IBDrecomb can be applied to sequenced population cohorts to obtain high-resolution, population-specific recombination maps. In simulated admixed data, IBDrecomb obtains higher accuracy than admixture-based estimation of recombination rates. When applied to 2,500 simulated individuals, IBDrecomb obtains similar accuracy to a linkage-disequilibrium (LD)-based method applied to 96 individuals (the largest number for which computation is tractable). Compared to LD-based maps, our IBD-based maps have the advantage of estimating recombination rates in the recent past rather than the distant past. We used IBDrecomb to generate new recombination maps for European Americans and for African Americans from TOPMed sequence data from the Framingham Heart Study (1,626 unrelated individuals) and the Jackson Heart Study (2,046 unrelated individuals), and we compare them to LD-based, admixture-based, and family-based maps.

Indexed as

Black or African AmericanGenetics, PopulationGenome, HumanHaplotypesHumansLinkage DisequilibriumPolymorphism, Single NucleotideRecombination, GeneticWhite People

Identifiers

PMID32533945
PMCPMC7332656
OpenAlexW3034735081

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.