Evidence map›Paper›PMID 40661451›Full record

ArticlebioRxiv : the preprint server for biology2025

Improved chromatin QTL mapping with CACTI.

Lili Wang, Xuanyao Liu

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

2 authors.

Lili WangThe Committee on Genetics, Genomics and Systems Biology, University of Chicago, Chicago, IL, USA.
Xuanyao LiuThe Committee on Genetics, Genomics and Systems Biology, University of Chicago, Chicago, IL, USA.

Funding

Statistical Methods to Study the Genetic Basis and Mechanisms of Trans Gene RegulationR35GM138084 · NIGMS · UNIVERSITY OF CHICAGO · PI LIU, XUANYAO · 2020 to 2024
$2.0M
NIGMS NIH HHS R35 GM138084
6 · The paper itself

Abstract

Mapping chromatin quantitative trait loci (cQTLs) is crucial for elucidating the regulatory mechanisms governing gene expression and complex traits. However, current cQTL mapping methods suffer from limited detection power, particularly at existing sample sizes, and are constrained by peak-calling accuracy. To address these limitations, we present CACTI, a novel method that improves cQTL mapping by leveraging correlations between neighboring regulatory elements. Across diverse histone marks (H3K4me1, H3K4me3, H3K27ac, H3K27me3 and H3K36me3) and cell types, CACTI identifies 51%-255% more cQTL signals compared to conventional single-peak-based approaches. Using CACTI, we generate a comprehensive cQTL map for the five histone marks across multiple cell types and perform colocalization analyses with GWAS loci from 44 complex traits. CACTI cQTLs colocalize with 6%-47% of GWAS loci, which is on average 15%-424% more than the standard cQTL mapping method across different marks. 24%-75% of colocalized GWAS loci show no colocalization with eQTLs. This underscores CACTI's unique ability to uncover regulatory mechanisms that would otherwise remain undetected by eQTL analysis alone, significantly improving the functional interpretation of GWAS findings.

Identifiers

PMID40661451
PMCPMC12258942

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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.