Get Confident Peaks From ChIP_SR replicates
This workflow takes as input SR BAM from ChIP-seq. It calls peaks on each replicate and intersect them. In parallel, each BAM is subsetted to smallest number of reads. Peaks are called using all subsets combined. Only peaks called using a combination of all subsets which have summits intersecting the intersection of at least x replicates will be kept.
- Author(s):
- Release: 1.2
- License: MIT
- UniqueID: f71eee25-8402-41da-8284-5298656ab379
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.
- first part: