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Chromatin Immunoprecipitation- ChIP

Chromatin Immunoprecipitation- ChIP

Chromatin immunoprecipitation, or ChIP, is an antibody-based technique used to identify sites on DNA that bind to transcription factors of interest or histone proteins. It also helps determine the type of histone modifications such as acetylation, phosphorylation, or methylation.
Types of ChIP
ChIP can be divided into two types - X-ChIP and N-ChIP. X-ChIP involves in vivo cross-linking of histones and regulatory proteins to DNA, fragmenting the DNA by sonication, and isolating the protein-DNA...

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Related Experiment Video

Updated: Jul 13, 2025

Capturing Chromosome Conformation Across Length Scales

Capturing Chromosome Conformation Across Length Scales

Published on: January 20, 2023

scHiCDiff: detecting differential chromatin interactions in single-cell Hi-C data.

Huiling Liu¹, Wenxiu Ma¹

¹Department of Statistics, University of California Riverside, Riverside, CA 92521, United States.

Bioinformatics (Oxford, England)

|October 17, 2023

Summary

This summary is machine-generated.

scHiCDiff software identifies differential chromatin interactions in single-cell Hi-C data. This tool effectively detects cell type-specific chromatin structure variations between conditions using robust statistical models.

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Last Updated: Jul 13, 2025

Capturing Chromosome Conformation Across Length Scales

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Published on: January 20, 2023

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Deciphering High-Resolution 3D Chromatin Organization via Capture Hi-C

Published on: October 14, 2022

In-Nucleus Hi-C in Drosophila Cells

In-Nucleus Hi-C in Drosophila Cells

Published on: September 15, 2021

Area of Science:

Genomics
Computational Biology
Epigenetics

Background:

Single-cell Hi-C data enables high-resolution analysis of 3D genome organization.
Understanding cell type-specific chromatin interactions is crucial for deciphering gene regulation.

Purpose of the Study:

To introduce scHiCDiff, a novel software tool for detecting differential chromatin interactions (DCIs) from single-cell Hi-C data.
To provide both nonparametric tests and parametric models for robust DCI detection.

Main Methods:

Implementation in R, freely available on GitHub.
Evaluation using simulated and real single-cell Hi-C datasets.
Utilizing nonparametric tests and parametric models, including a zero-inflated negative binomial model.

Main Results:

scHiCDiff effectively detects reliable and consistent single-cell DCIs between conditions.
The zero-inflated negative binomial model option shows particular efficacy.
The tool facilitates the study of cell type-specific chromatin structure variations.

Conclusions:

scHiCDiff is a valuable tool for analyzing single-cell chromatin interaction differences.
It enhances the study of cell-specific 3D genome organization.
The software supports research into the functional implications of chromatin structure variation.