Analyzing epigenome data in context of genome evolution and human diseases

Area of Science:

• Bioinformatics
• Computational Biology
• Genomics

Background:

• Epigenetic modifications play crucial roles in gene regulation, cellular differentiation, and disease development.
• Understanding epigenome differences across species and between healthy and diseased states is vital for biological and medical research.

Purpose of the Study:

• To describe and illustrate the use of web-based bioinformatic tools for analyzing epigenome data.
• To demonstrate a workflow for comparing epigenomic features, such as CpG islands, between species (human and mouse).
• To highlight the utility of scripting languages for in-depth epigenetics research, particularly for human diseases.

Main Methods:

• Utilized the Galaxy Web service to retrieve gene coordinates for orthologous genes in human and mouse.
• Employed EpiGRAPH, a web-based tool, for identifying statistically significant epigenetic differences between genomic regions.
• Leveraged the R statistical programming language for advanced epigenome data analysis and visualization.

Main Results:

• Successfully demonstrated a workflow integrating multiple web-based tools for comparative epigenome analysis.
• Identified key steps in analyzing CpG island evolution between human and mouse using bioinformatic pipelines.
• Showcased how R facilitates complex analyses of epigenetics in human diseases, offering insights beyond standard web tools.

Conclusions:

• Web-based bioinformatic tools provide an accessible entry point for epigenome data analysis.
• Combining web tools with scripting languages like R enhances the ability to explore complex epigenomic datasets.
• This approach is valuable for comparative epigenomics and understanding the molecular basis of human diseases.