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Updated: Jun 4, 2026
24:02
The ChroP Approach Combines ChIP and Mass Spectrometry to Dissect Locus-specific Proteomic Landscapes of Chromatin
Published on: April 11, 2014
MINTsC learns multi-way chromatin interactions from single cell high throughput chromatin conformation data.
Kwangmoon Park1, Tianchuan Gao2, Jingwen Yan2
1Department of Statistics, University of Wisconsin - Madison, Madison, WI, USA.
Nature Communications
|June 2, 2026
Summary
This study introduces MINTsC, a new framework for analyzing multi-way chromatin interactions in single-cell Hi-C (scHi-C) data. MINTsC effectively identifies complex genomic interactions, advancing our understanding of gene regulation and genetic associations.
Area of Science:
- Genomics
- Computational Biology
- Epigenetics
Background:
- Single-cell Hi-C (scHi-C) captures 3D genome organization but is under-utilized.
- Current analyses often overlook multi-way chromatin interactions, focusing on pairwise ones.
- Understanding complex chromatin interactions is crucial for deciphering gene regulation.
Purpose of the Study:
- To introduce MINTsC, a novel framework for learning and analyzing multi-way chromatin interactions from scHi-C data.
- To address the under-utilization of scHi-C data by enabling the study of complex genomic interactions.
- To provide a robust method for inferring multi-way interactions and their potential biological significance.
Main Methods:
- Developed MINTsC, a framework utilizing a dirichlet-multinomial spline model.
- Aggregated pairwise interactions across cells to generate multi-way interaction scores.
- Employed order statistics of pairwise test statistics for summarization and implemented well-calibrated p-values for FDR control.
Main Results:
- MINTsC successfully infers multi-way chromatin interactions from scHi-C datasets.
- Evaluations using cell lines and complex tissues, supported by external genomic data, validate MINTsC's findings.
- Application to human prefrontal cortex data revealed multi-way interactions suggesting multi-enhancer gene regulation.
Conclusions:
- MINTsC effectively learns and quantifies multi-way chromatin interactions from scHi-C data.
- Inferred multi-way interactions have potential applications in molecular quantitative trait locus (mQTL) and epistasis studies.
- MINTsC significantly reduces the multiple-testing burden in genetic association studies, enhancing discovery power.
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