Evidence map›Paper›PMID 42615977›Full record

ArticleBioinformatics (Oxford, England)2026

Assessing reproducibility of Hi-C chromatin interactions using stratum-adjusted irreproducible discovery rate.

Chen Xue, Feipeng Zhang, Qunhua Li

Abstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 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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0cells of the map it votes in
0citing papers in PubMed
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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

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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

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.

Chen XueDepartment of Statistics, The Pennsylvania State University, University Park, PA 16802, United States.ORCID 0009-0003-1375-1196
Feipeng ZhangSchool of Economics and Finance, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, PR China.
Qunhua LiDepartment of Statistics, The Pennsylvania State University, University Park, PA 16802, United States.ORCID 0000-0003-0675-7648

Funding

Statistical methods for improving reproducibility and utility of sequencing dataR01GM109453 · NIGMS · PENNSYLVANIA STATE UNIVERSITY, THE · PI LI, QUNHUA · 2013 to 2022
$2.3M
NIGMS NIH HHS R01 GM109453NIH HHS R01 GM109453
6 · The paper itself

Abstract

motivationHi-C is a powerful technology for mapping chromatin interactions genome-wide. However, interaction loops identified from Hi-C contact maps often vary across replicate experiments due to experimental noise, making reproducibility assessment essential. A major challenge lies in the genomic distance dependence of interaction strength, which systematically affects reproducibility but is overlooked by existing methods for reproducibility assessment.

resultsWe introduce Stratum-Adjusted Irreproducible Discovery Rate (SIDR), a novel statistical model that integrates distance stratification into the widely-used Irreproducible Discovery Rate (IDR) framework. SIDR explicitly models the confounding effect of genomic distance, enabling global control of irreproducibility across interaction ranges. Through simulations and real Hi-C datasets, we demonstrate that SIDR improves discriminative power and recovers more biologically meaningful interactions than existing approaches, making it a valuable tool for robust and reproducible Hi-C analysis. AVAILABILITY: The R package SIDR is freely available on GitHub https://github.com/qunhualilab/SIDR.

Indexed as

ChromatinComputational BiologyGenomicsReproducibility of ResultsSoftwareChromatin

Identifiers

PMID42615977
PMCPMC13509955

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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.