dinoR

dinoR tests for significant differences in NOMe-seq footprints between two conditions using genomic regions of interest centered around a landmark such as a transcription factor motif.

Key Features:

• NOMe-seq Data Input: Accepts NOMe-seq data (GCH methylation/protection) in the form of a Ranged Summarized Experiment.
• Footprint Categorization: Groups sequencing fragments into 3 or 5 categories representing characteristic footprints (TF bound, nucleosome bound, open chromatin).
• Visualization: Plots the percentage of fragments in each category as a heatmap or averaged across different ROI groups containing a common TF motif.
• Differential Analysis: Compares footprints between two sample groups using edgeR's quasi-likelihood methods on total fragment counts per ROI, sample, and footprint category.

Scientific Applications:

• Transcription Factor Footprinting: Analyzes TF binding patterns by examining NOMe-seq footprints around TF motifs.
• Chromatin Accessibility Profiling: Distinguishes between TF-bound, nucleosome-bound, and open chromatin states from NOMe-seq data.
• Condition Comparison: Identifies significant changes in chromatin organization and protein-DNA interactions between experimental conditions.

Methodology:

dinoR uses edgeR's quasi-likelihood methods on the total fragment counts per ROI, sample, and footprint category to test for significant differences between two sample groups.