ChIP-R is a method for assessing the reproducibility of replicated ChIP-seq type experiments. It incorporates the rank product method, a novel thresholding methods, and the use of peak fragmentation return the most reproducible peaks.
ChIP-R uses an adaptation of the rank product statistic to assess the reproducibility of ChIP-seq peaks by incorporating information from multiple ChIP-seq replicates and "fragmenting" peak locations to better combine the information present across the replicates.
- Python3.x with the following packages:
To install ChIP-R:
pip install ChIP-R
OR if you want to install from source:
git clone https://github.com/rhysnewell/ChIP-R.git cd ChIP-R python3 setup.py install
In the command line, type in 'chipr -h ' for detailed usage.
$ chipr -h usage: chipr [-h] -i INPUT [INPUT ...] [-o OUTPUT] [-m MINENTRIES] [--rankmethod RANKMETHOD] [--duphandling DUPHANDLING] [--seed RANDOM_SEED] [-a ALPHA] Combine multiple ChIP-seq files and return a union of all peak locations and a set confident, reproducible peaks as determined by rank product analysis optional arguments: -h, --help show this help message and exit -i INPUT [INPUT ...], --input INPUT [INPUT ...] ChIP-seq input files. These files must be in either narrowPeak, broadPeak, or regionPeak format. Multiple inputs are separeted by a single space -o OUTPUT, --output OUTPUT ChIP-seq output filename prefix -B, --bigbed Specify if input files are in BigBed format -m MINENTRIES, --minentries MINENTRIES The minimum peaks between replicates required to form an intersection of the peaks Default: 1 --rankmethod RANKMETHOD The ranking method used to rank peaks within replicates. Options: 'signalvalue', 'pvalue', 'qvalue'. Default: pvalue --duphandling DUPHANDLING Specifies how to handle entries that are ranked equally within a replicate Can either take the 'average' ranks or a 'random' rearrangement of the ordinal ranks Options: 'average', 'random' Default: 'average' --seed RANDOM_SEED Specify a seed to be used in conjunction with the 'random' option for -duphandling Must be between 0 and 1 Default: 0.5 -a ALPHA, --alpha ALPHA Alpha specifies the user cut-off value for set of reproducible peaks The analysis will still produce results including peaks within the threshold calculatedusing the binomial method Default: 0.05
$ chipr -i input_prefix1.bed input_prefix2.bed input_prefix3.bed input_prefix4.bed -m 2 -o output_prefix
Important result files:
- prefixname_ALL.bed: All intersected peaks, ordered from most significant to least (10 columns)
- prefixname_T2.bed: The tier 2 intersected peaks, the peaks that fall within the binomial threshold (10 columns)
- prefixname_T1.bed: The tier 1 intersected peaks, the peaks that fall within the user defined threshold (10 columns)
- prefixname_log.txt: A log containing the number of peaks appearing in each tier.
prefixname.bed file has 10 columns. The output follows the standard peak format for bed files, with the addition of a 10th column that specifies the ranks of the peaks that produced this possible peak. See the toy example below.
Authors: Rhys Newell, Michael Piper, Mikael Boden, Alexandra Essebier
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