Evidence map›Paper›PMID 40860341›Full record

ArticleFrontiers in genetics2025

Winner's curse in rare variant analysis: effect size estimation bias depends on effect direction and the association method used.

David Soave, Melisa Hayalioglu, Lei Sun

Abstract read
In one paragraph

Article in Frontiers in genetics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

David SoaveDepartment of Mathematics, Wilfrid Laurier University, Waterloo, ON, Canada.
Melisa HayaliogluDepartment of Mathematics, Wilfrid Laurier University, Waterloo, ON, Canada.
Lei SunDepartment of Statistical Sciences, University of Toronto, Toronto, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

For complex human traits, a large portion of genetic heritability remains unaccounted for beyond common genetic variants; therefore, estimating the contribution of rare variants (RVs) to the etiology of complex traits is of interest. Research in this domain has primarily focused on gene-based RV testing methods, in which information from multiple variants is combined to maximize statistical power in detecting genes associated with the trait of interest. However, after discovering an association, estimating individual effects becomes challenging due to sample size limitations. Hence, the focus may shift to estimating the average genetic effect (AGE) for the group of RVs analyzed. This study demonstrates that both AGEs and individual variant effects can be influenced by competing

Indexed as

effect heterogeneityestimationgenome-wide association studyjoint analysisrare variantsselection biaswinner’s curse

Identifiers

PMID40860341
PMCPMC12370714

What OpenQuestion holds

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Registered trials

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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.