DiffBind TF Differential Binding Analysis

Overview

This skill enables comprehensive differential TF binding analysis using DiffBind in R. DiffBind integrates read counting, normalization, and statistical modeling to identify differentially bound peaks between conditions.

To perform DiffBind differential binding analysis:

• Initialize the project directory.
• Refer to the Inputs & Outputs section to check inputs and build the output architecture. All the output file should located in ${proj_dir} in Step 0.
• Always prompt user if required files are missing.
• Provide a sample sheet with ChIP-seq peak files and corresponding BAM files for each sample.
• Construct a DBA object from the sample sheet.
• Compute read counts over consensus peak regions.
• Specify experimental conditions (e.g., treatment vs. control or cell_type_A vs. cell_type_B).
• Run statistical tests to identify differentially bound regions.
• Generate correlation heatmaps, PCA plots, and volcano plots; extract significant binding events.