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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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Updated: Dec 25, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

Published on: December 10, 2012

HiChIP-Peaks: a HiChIP peak calling algorithm.

Chenfu Shi¹, Magnus Rattray^2,3, Gisela Orozco^1,3

¹Division of Musculoskeletal and Dermatological Sciences, School of Biological Sciences, Centre for Genetics and Genomics Versus Arthritis.

Bioinformatics (Oxford, England)

|March 25, 2020

Summary

This summary is machine-generated.

We developed HiChIP-Peaks to reliably identify chromatin looping anchors from HiChIP data. This tool improves peak discovery and enables quantitative comparison across samples, overcoming limitations of existing methods.

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Last Updated: Dec 25, 2025

A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types

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Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Author Spotlight: A Computational Pipeline for Analyzing Chimeric Noncoding RNA-Target RNA Interactions in High-Throughput Sequencing Data

Published on: December 1, 2023

Area of Science:

Genomics
Molecular Biology
Bioinformatics

Background:

High-throughput Chromosome Conformation Capture (HiChIP) is essential for studying 3D chromatin organization.
Existing tools for HiChIP data analysis require accurate loop anchor identification, which is currently challenging.
Current methods suffer from high false discovery rates and dependency on sequencing depth, limiting quantitative comparisons.

Purpose of the Study:

To develop a novel computational tool for robust peak identification in HiChIP data.
To enhance the reliability and recall rate of chromatin loop discovery tools.
To enable quantitative analysis and differential peak analysis across multiple HiChIP samples.

Main Methods:

Developed HiChIP-Peaks, a tool utilizing a re-ligation site-centric representation of HiChIP data.
Implemented a method for read counting to facilitate differential peak analysis.
Focused on improving peak identification independent of sequencing depth.

Main Results:

HiChIP-Peaks accurately identifies peaks from HiChIP datasets, improving downstream loop discovery.
The tool enhances reliability and recall rate, even with reduced sequencing depth.
A quantitative method for comparing peaks across samples is provided, enabling differential analysis.

Conclusions:

HiChIP-Peaks offers a significant advancement in analyzing HiChIP data for 3D chromatin organization studies.
The tool addresses key limitations of existing methods, improving data interpretation and quantitative comparisons.
HiChIP-Peaks facilitates more comprehensive insights into chromatin looping mechanisms.