Evidence map›Paper›PMID 22267498›Full record

ArticleGenetics2012

Detecting rare variant associations by identity-by-descent mapping in case-control studies.

Sharon R Browning, Elizabeth A Thompson

Abstract read
In one paragraph

Article in Genetics, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 81 papers.

0numbers the graph read from it
0cells of the map it votes in
81citing 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

81 citing papers in PubMed.

  1. Article
  2. HiFiMAP: High-resolution fast identity-by-descent mapping test.medRxiv : the preprint server for health sciences · 2026
    Article
  3. Article
  4. Article
  5. Article
  6. Identity-by-descent segments in large samples.Theoretical population biology · 2025
    Article
  7. Article
  8. Mathematical bounds on rTheoretical population biology · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Fast simulation of identity-by-descent segments.Bulletin of mathematical biology · 2025
    Article
  13. Article
  14. Fast simulation of identity-by-descent segments.bioRxiv : the preprint server for biology · 2025
    Article
  15. Mathematical bounds onbioRxiv : the preprint server for biology · 2024
    Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

21 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.

Sharon R BrowningDepartment of Biostatistics, University of Washington, Seattle, Washington 98195, USA. sguy@uw.edu
Elizabeth A Thompson

Funding

Statistical Methods for X-Chromosome Genetic DataP01GM099568 · NIGMS · UNIVERSITY OF WASHINGTON · PI WEIR, BRUCE S. · 2012 to 2016
$7.3M
Improved gene mapping for whole genome dataR01HG005701 · NHGRI · UNIVERSITY OF WASHINGTON · PI BROWNING, BRIAN LEE · 2010 to 2024
$4.4M
Methods for the Genetic Epidemiology of Complex TraitsR37GM046255 · NIGMS · UNIVERSITY OF WASHINGTON · PI THOMPSON, ELIZABETH ALISON · 2008 to 2017
$4.2M
NHGRI NIH HHS R01 HG005701NHGRI NIH HHS R01HG005701NIGMS NIH HHS P01 GM099568NIGMS NIH HHS R01GM057091NIGMS NIH HHS R37 GM046255NIGMS NIH HHS R37GM046255Wellcome Trust 076113
6 · The paper itself

Abstract

Identity-by-descent (IBD) mapping tests whether cases share more segments of IBD around a putative causal variant than do controls. These segments of IBD can be accurately detected from genome-wide SNP data. We investigate the power of IBD mapping relative to that of SNP association testing for genome-wide case-control SNP data. Our focus is particularly on rare variants, as these tend to be more recent and hence more likely to have recent shared ancestry. We simulate data from both large and small populations and find that the relative performance of IBD mapping and SNP association testing depends on population demographic history and the strength of selection against causal variants. We also present an IBD mapping analysis of a type 1 diabetes data set. In those data we find that we can detect association only with the HLA region using IBD mapping. Overall, our results suggest that IBD mapping may have higher power than association analysis of SNP data when multiple rare causal variants are clustered within a gene. However, for outbred populations, very large sample sizes may be required for genome-wide significance unless the causal variants have strong effects.

Indexed as

Genome, HumanPopulation DensityCase-Control StudiesChromosome MappingComputer SimulationDemographyDiabetes Mellitus, Type 1Gene FrequencyGenotyping TechniquesHLA AntigensHumansPedigreePolymorphism, Single NucleotideQuantitative Trait, HeritableSelection, GeneticHLA Antigens

Identifiers

PMID22267498
PMCPMC3316661

What OpenQuestion holds

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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.