Multiple conda environments involved to use all these tools together.

• Starting from raw Fastq files
• Trimming task using cutadapt
• Alignment task using STAR
• Check raw data quality using MultiQC

• Using RADAR package
  • It only works for peak-calling and differential methylation analysis at once (samples at two conditions)
  • (it has multiprocessing option then it works faster)
• Gene level methylation enrichment and pathway analysis using iPAGE If study design has no differential analysis:
• Using exomePeak package
  • It also works with samples which are only at one condition

• Draw metagene plots using Guitar package
• Motif analysis to check DRACH & RGAC motif presentation using FIRE algorithm

• Draw histogram using ggplot2 package (easy!)
• Using wilcox-test and t-test to confirm global hyper or hypo methylation among significant peaks

• Select hyper/hypo gene sets (genes with logFC above/under a threshold) using awk command (easy!)
• Evaluate enrichment within other high-throughput datasets using a module from TIESER algorithm
  • It works through Mutual Information (MI) evaluation same as FIRE and iPAGE