Evidence map›Paper›PMID 40911511›Full record

ArticleGenetics2026

Phantom epistasis through the lens of genealogies.

Anastasia Ignatieva, Lino A F Ferreira

Abstract read
In one paragraph

Article in Genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

1 citing paper in PubMed.

  1. Interactions with polygenic background impact quantitative traits in the UK Biobank.medRxiv : the preprint server for health sciences · 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

2 authors.

Anastasia IgnatievaDepartment of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom.ORCID 0000-0001-6402-9396
Lino A F FerreiraDepartment of Statistics, University of Oxford, Oxford OX1 3LB, United Kingdom.ORCID 0000-0002-1957-4245

Funding

Wellcome TrustWellcome Trust 22334/Z/21/Z
6 · The paper itself

Abstract

Phantom epistasis arises when, in the course of testing for gene-by-gene interactions, the omission of a causal variant with a purely additive effect on the phenotype causes the spurious inference of a significant interaction between two single-nucleotide polymorphisms (SNPs). This is more likely to arise when the two SNPs are in relatively close proximity, so while true epistasis between nearby variants could be commonplace, in practice there is no reliable way of telling apart true epistatic signals from false positives. By considering the causes of phantom epistasis from a genealogy-based perspective, we leverage the rich information contained within reconstructed genealogies (in the form of ancestral recombination graphs) to address this problem. We propose a novel method for explicitly quantifying the genealogical evidence that a given pairwise interaction is the result of phantom epistasis, which can be applied to pairs of SNPs regardless of the genetic distance between them. Our method uses only publicly available data and so does not require access to the phenotypes and genotypes used for detecting interactions. Using simulations, we show that the method has excellent performance at even low distances (around 0.5 Mb), and demonstrate its power to detect phantom epistasis using real data from previous studies. This opens up the exciting possibility of distinguishing spurious interactions in cis from those reflecting real biological effects.

Indexed as

Epistasis, GeneticModels, GeneticPedigreeComputer SimulationGenotypeHumansPhenotypePolymorphism, Single Nucleotideancestral recombination graphsgene-by-gene interactionsgenome-wide association studiesphantom epistasis

Identifiers

PMID40911511
PMCPMC12774852

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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.