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Chromatin Immunoprecipitation- ChIP

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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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相关实验视频

Updated: Jan 15, 2026

Capturing Chromosome Conformation Across Length Scales

Capturing Chromosome Conformation Across Length Scales

Published on: January 20, 2023

PB-DiffHiC:一种统计框架,用于从高分辨率伪批量Hi-C数据中检测差异色素相互作用.

Yan Zhou¹, Yaohua Hu¹, Liuting Tan¹

¹School of Mathematical Sciences, Institute of Statistical Sciences, Shenzhen University, Shenzhen, China.

|October 9, 2025

概括

PB-DiffHiC提供了一种强大的方法,用于分析高分辨率单细胞Hi-C (scHi-C) 数据中的差异色素相互作用. 这种新的框架克服了数据稀疏性,提高了识别基因组结构变化的精度.

关键词:

3D基因组组织 3D基因组组织染色素的相互作用不同分析差异分析.这就是Hi-C差异.这是一种Hi-C单细胞体.伪散装的大量货物统计建模统计建模

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相关实验视频

Last Updated: Jan 15, 2026

Capturing Chromosome Conformation Across Length Scales

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Published on: January 20, 2023

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.

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Published on: May 6, 2010

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

科学领域:

基因组学和生物信息学
分子生物学分子生物学
计算生物学计算生物学

背景情况:

单细胞Hi-C (scHi-C) 允许对染色质相互作用进行详细分析,以了解基因组功能.
由于数据稀疏,分析高分辨率 (10Kb) scHi-C数据具有挑战性.
目前的方法,如归算或伪批量分析有局限性.

研究的目的:

开发一个强大的统计框架,用于使用原始伪批量scHi-C数据进行高分辨率差异色素相互作用分析.
为应对scHi-C分析中数据稀疏性所带来的挑战.
为现有方法提供一个计算效率高,可靠的替代方案.

主要方法:

开发了PB-DiffHiC,这是一个用于分析原始伪批量HiC数据的参数统计框架.
包含高斯卷积,短距离相互作用稳定性和Poisson建模用于规范化和测试.
与使用细胞类型特定的染色质循环和匹配的批量Hi-C数据的现有方法进行基准测试.

主要成果:

与替代方法相比,PB-DiffHiC在识别差异色素循环方面表现出更高的精度.
对伪批量和匹配批量Hi-C数据的分析显示出强烈的一致性,验证了PB-DiffHiC的可靠性.
在一个案例研究中成功确定了与Kcnq5相关的差异性相互作用,与其他方法保持一致.

结论:

PB-DiffHiC是用于高分辨率差异色素相互作用分析的统计学上健全和稳健的方法.
该框架有效地处理原始伪批量Hi-C数据,克服稀疏性的限制.
对于研究基因组结构功能关系的研究人员来说,PB-DiffHiC提供了一种有价值的工具.