ChromTag: an interactive R-shiny platform for analysis and visualization of CUT&Tag and ChIP-seq peak profiling data

Area of Science:

• Epigenomics
• Computational Biology
• Bioinformatics

Background:

• Chromatin profiling technologies (CUT&Tag, ChIP-seq) map histone modifications and transcription factor binding genome-wide.
• Interpreting complex epigenomic datasets requires significant technical expertise, limiting accessibility for many researchers.

Purpose of the Study:

• To develop an accessible, interactive web-based application for the comprehensive exploration and visualization of epigenomic profiling data.
• To provide a user-friendly solution for downstream analysis of CUT&Tag and ChIP-seq datasets.

Main Methods:

• Developed ChromTag, an R Shiny application with a modular workflow for epigenomic data analysis.
• Implemented differential peak detection, gene assignment, Gene Ontology (GO) and KEGG pathway enrichment analysis, and Gene Set Enrichment Analysis (GSEA).
• Integrated motif enrichment analysis and extensive visualization tools (volcano plots, PCA, heatmaps).

Main Results:

• ChromTag enables differential peak detection and functional annotation of CUT&Tag and ChIP-seq data.
• The platform supports pathway analysis (ORA, GSEA) and motif enrichment for identifying regulatory elements.
• Supports human, mouse, and Drosophila datasets with diverse visualization options.

Conclusions:

• ChromTag offers a practical and accessible downstream analysis solution for chromatin profiling data.
• The application bridges preprocessed data with interactive visualization and functional interpretation, empowering researchers.
• Facilitates deeper understanding of gene regulation, cellular differentiation, and disease mechanisms through accessible epigenomic data analysis.