R Tutorial: Detection of Differentially Interacting Chromatin Regions From Multiple Hi-C Datasets

Area of Science:

• Genomics
• Molecular Biology
• Bioinformatics

Background:

• Three-dimensional (3D) chromatin interactions are crucial for regulating gene expression and other genomic processes.
• High-throughput chromatin conformation capture (Hi-C) is a powerful technology for studying global chromatin structure and interactions.
• Comparative Hi-C experiments offer insights into dynamic changes in genome organization.

Purpose of the Study:

• To present a comprehensive workflow for analyzing and interpreting comparative Hi-C experiments.
• To guide users in obtaining, pre-processing, and analyzing Hi-C data.
• To facilitate the identification and interpretation of differentially interacting genomic regions.

Main Methods:

• Utilizing public Hi-C data repositories.
• Implementing pre-processing pipelines for raw Hi-C data.
• Applying normalization techniques for comparative analysis.
• Employing R packages such as multiHiCcompare, diffHic, and FIND R for differential interaction analysis.
• Visualizing and interpreting results of comparative Hi-C experiments.

Main Results:

• A detailed protocol for comparative Hi-C data analysis is provided.
• Suggestions for data acquisition, pre-processing, and normalization are offered.
• Three distinct R-based packages are presented for differential interaction analysis.
• Methods for visualizing and interpreting differentially interacting regions are discussed.

Conclusions:

• The presented workflow enables robust analysis and interpretation of comparative Hi-C data.
• This approach aids in understanding cell-type-specific gene expression and genomic regulation.
• The tutorial provides a practical guide for researchers using R for Hi-C data analysis.