Differential Region Analysis with DESeq2

Overview

This skill performs differential region analysis between experimental conditions using DESeq2 in a count-based framework. Main steps include:

• 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.
• Always prompt user for the threshold of qvalues and log2foldchange to define significant regions.
• Merge peaks across replicates or samples to build a consensus peak set.
• Generate read count matrix over peaks using featureCounts or bedtools.
• Prepare sample metadata file describing conditions and replicates.
• Perform differential analysis using DESeq2.
• Visualize and interpret results (PCA, volcano plot).
• Output significantly up and down accessible regions.