Evidence map›Paper›PMID 39962081›Full record

ArticleNature communications2025

Resolving discrepancies between chimeric and multiplicative measures of higher-order epistasis.

Uthsav Chitra, Brian Arnold, Benjamin J Raphael

Abstract read
In one paragraph

Article in Nature communications, 2025. 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

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

1 citing paper in PubMed.

  1. 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.

Uthsav Chitra *Department of Computer Science, Princeton University, Princeton, NJ, USA.
Brian Arnold *Department of Computer Science, Princeton University, Princeton, NJ, USA.
Benjamin J RaphaelDepartment of Computer Science, Princeton University, Princeton, NJ, USA. braphael@princeton.edu.ORCID http://orcid.org/0000-0003-1274-048X

Funding

Comprehensive and Robust Tools for Analysis of Tumor Heterogeneity and EvolutionU24CA248453 · NCI · PRINCETON UNIVERSITY · PI Benjamin Raphael · 2020 to 2026
$4.7M
Pathway, Network and Spatiotemporal Integration of Cancer Genomics DataU24CA264027 · NCI · PRINCETON UNIVERSITY · PI RAPHAEL, BENJAMIN, YEH, JEN JEN · 2021 to 2025
$1.5M
NCI NIH HHS U24 CA248453NCI NIH HHS U24 CA264027U.S. Department of Health & Human Services | NIH | National Cancer Institute (NCI) U24CA264027
6 · The paper itself

Abstract

Epistasis - the interaction between alleles at different genetic loci - plays a fundamental role in biology. However, several recent approaches quantify epistasis using a chimeric formula that measures deviations from a multiplicative fitness model on an additive scale, thus mixing two scales. Here, we show that for pairwise interactions, the chimeric formula yields a different magnitude but the same sign of epistasis compared to the multiplicative formula that measures both fitness and deviations on a multiplicative scale. However, for higher-order interactions, we show that the chimeric formula can have both different magnitude and sign compared to the multiplicative formula. We resolve these inconsistencies by deriving mathematical relationships between the different epistasis formulae and different parametrizations of the multivariate Bernoulli distribution. We argue that the chimeric formula does not appropriately model interactions between the Bernoulli random variables. In simulations, we show that the chimeric formula is less accurate than the classical multiplicative/additive epistasis formulae and may falsely detect higher-order epistasis. Analyzing multi-gene knockouts in yeast, multi-way drug interactions in E. coli, and deep mutational scanning of several proteins, we find that approximately 10% to 60% of inferred higher-order interactions change sign using the multiplicative/additive formula compared to the chimeric formula.

Indexed as

Epistasis, GeneticModels, GeneticAllelesComputer SimulationEscherichia coliMutationSaccharomyces cerevisiae

Identifiers

PMID39962081
PMCPMC11833126

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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.