Computational methods to explore chromatin state dynamics

Area of Science:

• Genomics
• Epigenetics
• Computational Biology

Background:

• Histone modifications and chromatin accessibility define genome organization and function.
• Epigenomic datasets map these marks, histone variants, and open chromatin regions.
• Statistical models annotate DNA and infer combinatorial chromatin states (CS).

Approach:

• This review surveys computational tools designed to analyze CS alterations.
• The focus is on tools that compare CS across two or more distinct cellular conditions.
• Methods capture dynamic changes in genomic function and activity.

Key Points:

• Histone modifications and chromatin accessibility map genome-wide epigenomic features.
• Chromatin states (CS) provide insights into genomic function, including gene bodies, promoters, and enhancers.
• CS are dynamic and vary between normal, preneoplastic, and tumor cells.

Conclusions:

• Computational tools are crucial for analyzing dynamic chromatin state changes.
• Understanding CS alterations aids in deciphering genomic function in various cellular contexts.
• This review highlights methods for capturing CS variations across different cell conditions.