Evidence map›Paper›PMID 42837436›Full record

ArticlePLoS computational biology2026

HiFIseek: Gene-specific enrichment of high-impact mutations in associated genomic regions.

Rafael Riudavets Puig, Denise G O'Mahony, Ina Skaara Brorson, Ksenia Sokolova, Vessela N Kristensen, Anthony Mathelier

Abstract read
In one paragraph

Article in PLoS computational biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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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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

6 authors.

Rafael Riudavets PuigNorwegian Center for Molecular Biosciences and Medicine (NCMBM), Nordic EMBL Partnership, University of Oslo, Oslo, Norway.ORCID https://orcid.org/0000-0002-2855-9952
Denise G O'MahonyDepartment of Medical Genetics, Oslo University Hospital, Oslo, Norway.ORCID https://orcid.org/0000-0002-7212-0920
Ina Skaara BrorsonDepartment of Medical Genetics, Oslo University Hospital, Oslo, Norway.ORCID https://orcid.org/0000-0001-6691-9413
Ksenia SokolovaPrinceton Precision Health, Princeton University, Princeton, New Jersey, United States of America.
Vessela N KristensenDepartment of Medical Genetics, Oslo University Hospital, Oslo, Norway.ORCID https://orcid.org/0000-0001-5012-7438
Anthony MathelierNorwegian Center for Molecular Biosciences and Medicine (NCMBM), Nordic EMBL Partnership, University of Oslo, Oslo, Norway.ORCID https://orcid.org/0000-0001-5127-5459

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcription is regulated through the sequence-specific binding of transcription factors (TFs) to cis-regulatory regions (CRRs); DNA variants in CRRs can disrupt TF-DNA interactions and gene regulatory networks through a cascading effect. Despite a few cases of reported recurrent cis-regulatory variants (CRVs), another approach for detecting non-coding functional events relies on combining gene-CRR associations capturing the regulatory elements controlling gene transcription, and functional impact (FI) scores quantifying the deleterious effect of variants. While many methods exist for each, how much they agree and how strongly the choice of CRR-FI score combination impacts the prediction of cis-regulatory altered genes has not been systematically assessed. Here, we demonstrate that gene-CRR associations and FI scoring methods exhibit little consensus, highlighting the impact of the choice of a specific CRR-FI score combination in a given analysis. These observations point to the need for a systematic approach to evaluate several gene-CRR and FI scoring methods in a unified framework. To address this gap, we developed HiFIseek, a Snakemake pipeline of two enrichment detection methods exploring the enrichment of high FI variants in CRRs associated with a gene using all region-score combinations. We applied HiFIseek to detect genes exhibiting high functional impact CRVs in eight cancer cohorts and a set of breast cancer risk-associated single-nucleotide polymorphisms (SNPs). We demonstrate that cancer driver genes exhibit a higher frequency of FI CRVs compared to non-cancer genes. In the cancer cohorts, HiFIseek detected genes pointing to cancer-related pathways with enrichment for high FI CRVs despite a small degree of agreement across CRR-FI score combinations. In the SNP cohort, HiFIseek found again small consensus across CRR-score combinations, one of which returned 18 known cancer-related genes, including BRCA1, showing an enrichment of high-impact CRVs.

Indexed as

Computational BiologyGenomicsMutationRegulatory Sequences, Nucleic AcidSoftwareBreast NeoplasmsHumansPolymorphism, Single NucleotideTranscription FactorsTranscription Factors

Identifiers

PMID42837436
PMCPMC13657309

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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.