Evidence map›Paper›PMID 21565292›Full record

SynthesisAmerican journal of human genetics2011

Random-effects model aimed at discovering associations in meta-analysis of genome-wide association studies.

Buhm Han, Eleazar Eskin

Abstract readMeta-Analysis
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in American journal of human genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 441 papers, 64 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
441citing papers in PubMed, 64 pooled it
–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

441 citing papers in PubMed, 64 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Pooled it
  9. Pooled it
  10. IL31 identified as a key genetic risk factor for prurigo nodularis.The Journal of allergy and clinical immunology · 2025
    Pooled it
  11. Pooled it
  12. Pooled it
  13. Assessing theRMD open · 2025
    Pooled it
  14. Pooled it
  15. Pooled it
  16. Pooled it
  17. Pooled it
  18. Pooled it
  19. Pooled it
  20. Pooled it

381 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.

Buhm HanDepartment of Computer Science, University of California-Los Angeles, CA, USA.
Eleazar Eskin

Funding

Substance Abuse & Behavioral Disinhibition: Integrating Genes & EnvironmentU01DA024417 · NIDA · UNIVERSITY OF MINNESOTA · PI IACONO, WILLIAM G. · 2007 to 2010
$10.8M
Discovering the Genetic Basis of HypertensionK25HL080079 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI ESKIN, ELEAZAR · 2006 to 2010
$685k
NHLBI NIH HHS K25 HL080079NHLBI NIH HHS K25-HL080079NIDA NIH HHS U01 DA024417NIDA NIH HHS U01-DA024417NIEHS NIH HHS N01 ES045530
6 · The paper itself

Abstract

Meta-analysis is an increasingly popular tool for combining multiple different genome-wide association studies (GWASs) in a single aggregate analysis in order to identify associations with very small effect sizes. Because the data of a meta-analysis can be heterogeneous, referring to the differences in effect sizes between the collected studies, what is often done in the literature is to apply both the fixed-effects model (FE) under an assumption of the same effect size between studies and the random-effects model (RE) under an assumption of varying effect size between studies. However, surprisingly, RE gives less significant p values than FE at variants that actually show varying effect sizes between studies. This is ironic because RE is designed specifically for the case in which there is heterogeneity. As a result, usually, RE does not discover any associations that FE did not discover. In this paper, we show that the underlying reason for this phenomenon is that RE implicitly assumes a markedly conservative null-hypothesis model, and we present a new random-effects model that relaxes the conservative assumption. Unlike the traditional RE, the new method is shown to achieve higher statistical power than FE when there is heterogeneity, indicating that the new method has practical utility for discovering associations in the meta-analysis of GWASs.

Indexed as

Models, GeneticCrohn DiseaseDiabetes Mellitus, Type 2Genome-Wide Association StudyHumansLikelihood FunctionsModels, StatisticalQuantitative Trait Loci

Identifiers

PMID21565292
PMCPMC3146723

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.