ArticleBMC bioinformatics2018
HiCcompare: an R-package for joint normalization and comparison of HI-C datasets.
Article in BMC bioinformatics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers.
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85 citing papers in PubMed.
- BRWD1 directs B cell epigenetic states required for germinal center initiation, maintenance and function.Nature communications · 2026Article
- Neuronal activity-driven 3D chromatin dynamics in cortical pyramidal neurons depend on SATB2.Nucleic acids research · 2026Article
- Downregulated transcription in chromosomal domains of midbrain dopamine neurons linked to schizophrenia.Nature communications · 2026Article
- PDS5A and TOP2B cooperate for chromatin recruitment via CTCF.bioRxiv : the preprint server for biology · 2026Article
- Differential chromatin looping regulated by two GA-binding transcription factors creates an X-specific chromatin environment for dosage compensation.bioRxiv : the preprint server for biology · 2026Article
- Topologically associating domains define the 3D genome architecture of mouse totipotent-like stem cells.The Journal of biological chemistry · 2026Article
- Differential analysis of image-based chromatin tracing data with Dory.bioRxiv : the preprint server for biology · 2026Article
- Multi-dimensional epigenomic dynamics converge on H3K4-mediated regulation of low-COPlant communications · 2025Article
- DiffHiChIP: Identifying differential chromatin contacts from HiChIP data.Cell reports methods · 2025Article
- DNA G-quadruplex profiling in skeletal muscle stem cells reveals functional and mechanistic insights.Genome biology · 2025Article
- Integrated analysis of differential intra-chromosomal community interactions: A study of breast cancer.Artificial intelligence in medicine · 2025Article
- scHiCcompare: An R Package for Differential Analysis of Single-cell Hi-C Data.Journal of molecular biology · 2025Article
- SMCHD1 maintains heterochromatin, genome compartments and epigenome landscape in human myoblasts.Nature communications · 2025Article
- Physiological role and mechanisms of action for a long noncoding haplotype region.Cell reports · 2025Article
- EBNA leader protein orchestrates chromatin architecture remodeling during Epstein-Barr virus-induced B cell transformation.Nucleic acids research · 2025Article
- Methyl-Micro-C: simultaneous characterization of chromatin accessibility, interactions, and DNA methylation.NAR genomics and bioinformatics · 2025Article
- KDM4C inhibition blocks tumor growth in basal breast cancer by promoting cathepsin L-mediated histone H3 cleavage.Nature genetics · 2025Article
- Mutant CEBPA promotes tolerance to inflammatory stress through deficient AP-1 activation.Nature communications · 2025Article
- A comprehensive review and benchmark of differential analysis tools for Hi-C data.Briefings in bioinformatics · 2025Review
- Read Mapping for Hi-C Analysis.Methods in molecular biology (Clifton, N.J.) · 2025Article
25 more citing papers are in PubMed but not listed here.
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4 authors.
Funding
Abstract
backgroundChanges in spatial chromatin interactions are now emerging as a unifying mechanism orchestrating the regulation of gene expression. Hi-C sequencing technology allows insight into chromatin interactions on a genome-wide scale. However, Hi-C data contains many DNA sequence- and technology-driven biases. These biases prevent effective comparison of chromatin interactions aimed at identifying genomic regions differentially interacting between, e.g., disease-normal states or different cell types. Several methods have been developed for normalizing individual Hi-C datasets. However, they fail to account for biases between two or more Hi-C datasets, hindering comparative analysis of chromatin interactions.
resultsWe developed a simple and effective method, HiCcompare, for the joint normalization and differential analysis of multiple Hi-C datasets. The method introduces a distance-centric analysis and visualization of the differences between two Hi-C datasets on a single plot that allows for a data-driven normalization of biases using locally weighted linear regression (loess). HiCcompare outperforms methods for normalizing individual Hi-C datasets and methods for differential analysis (diffHiC, FIND) in detecting a priori known chromatin interaction differences while preserving the detection of genomic structures, such as A/B compartments.
conclusionsHiCcompare is able to remove between-dataset bias present in Hi-C matrices. It also provides a user-friendly tool to allow the scientific community to perform direct comparisons between the growing number of pre-processed Hi-C datasets available at online repositories. HiCcompare is freely available as a Bioconductor R package https://bioconductor.org/packages/HiCcompare/ .
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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.