Consensus peaks Workflow

The goal of this workflow is to get a list of confident peaks with summits from n replicates.

Inputs dataset

• The workflow needs a single input which is a list of datasets with n BAM where PCR duplicates have been removed (the workflow also works for nested list if you have multiple conditions each with multiple replicates).

Inputs values

• Minimum number of overlap: Minimum number of replicates into which the final summit should be present.
• effective_genome_size: this is used by MACS2 and may be entered manually (indications are provided for heavily used genomes).
• bin_size: this is the bin sized used to compute the average of normalized profiles. Large values will allow to have a smaller output file but with less resolution while small values will increase computation time and size of the output file to produce a more resolutive bigwig.

Strategy summary

Here is a generated example to highlight the strategy:

Processing

• The workflow will:
  • first part:
    • call peaks and compute normalized coverage on each BAM individually
    • average normalized profiles
    • compute the intersection between all peaks and filter when at least x replicate overlaps
  • second part:
    • subset all BAM to get the same number of reads
    • call peaks on all subsetted BAM combined
  • finally, keep only peaks from the second part that have summits overlapping the filtered intersection of the first part.