ArticleMethods in molecular biology (Clifton, N.J.)2022
Methods for the Differential Analysis of Hi-C Data.
Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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.
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.
Who cites it
5 citing papers in PubMed, 8 citations in OpenAlex.
- Integrated analysis of differential intra-chromosomal community interactions: A study of breast cancer.Artificial intelligence in medicine · 2025Article
- A comprehensive review and benchmark of differential analysis tools for Hi-C data.Briefings in bioinformatics · 2025Review
- HiCMC: High-Efficiency Contact Matrix Compressor.BMC bioinformatics · 2024Article
- SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single-cell Hi-C data.Briefings in bioinformatics · 2023Article
- The 3D genome and its impacts on human health and disease.Life medicine · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The 3D organization of chromatin within the nucleus enables dynamic regulation and cell type-specific transcription of the genome. This is true at multiple levels of resolution: on a large scale, with chromosomes occupying distinct volumes (chromosome territories); at the level of individual chromatin fibers, which are organized into compartmentalized domains (e.g., Topologically Associating Domains-TADs), and at the level of short-range chromatin interactions between functional elements of the genome (e.g., enhancer-promoter loops).The widespread availability of Chromosome Conformation Capture (3C)-based high-throughput techniques has been instrumental in advancing our knowledge of chromatin nuclear organization. In particular, Hi-C has the potential to achieve the most comprehensive characterization of chromatin 3D interactions, as it is theoretically able to detect any pair of restriction fragments connected as a result of ligation by proximity.This chapter will illustrate how to compare the chromatin interactome in different experimental conditions, starting from pre-computed Hi-C contact matrices, how to visualize the results, and how to correlate the observed variations in chromatin interaction strength with changes in gene expression.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.