ROCCO: [R]obust [O]pen [C]hromatin Detection via [C]onvex [O]ptimization
What
ROCCO is an efficient algorithm for detection of "consensus peaks" in large datasets with multiple HTS data samples, where an enrichment in read counts/densities is observed in a nontrivial subset of samples.
Input/Output
- Input: Samples'
.bamalignments (-i) and a reference genome assembly (-g) for chromosome sizes - Output: BED file of consensus peak regions (Default format is BED3:
chrom,start,end). narrowPeak and gappedPeak outputs are supported for BAM inputs. Use--peak_mode both.
How
ROCCO models consensus peak calling as an optimization problem: select the most enriched genomic regions as peaks while controlling total genomic coverage and discouraging fragmented calls.
- Enrichment is measured by a read density score in the selected genomic regions
- Budget proportions calibrate selection penalties that control total genomic coverage
- Fragmentation is controlled via a total variation penalty, multiplied by a penalty parameter $\gamma$ ($\gamma \sum_i |x_{i+1} - x_i|$).
Why
- Consideration of enrichment magnitude and spatial characteristics of open chromatin signals
- Scaling to large sample sizes (100+)
- Unsupervised Does not require training data or a heuristically determined set of initial candidate peak regions
- Less rigid thresholds with respect to the minimum number/width of supporting samples/replicates.
- Mathematically tractable model permitting worst-case analysis of runtime and performance
Basic Usage
Run rocco --help for the complete command-line reference.
ROCCO accepts either one or more BAM files, separated by spaces.
rocco -i <BAM> [<BAM> ...] \
-g <GENOME> \
-o <OUTPUT.bed>
Genome assemblies hg38, hg19, mm10, mm39, and dm6 can be used with -g, to supply a built-in chromosome sizes file (canonical chromosomes only) and effective genome size.
If using ROCCO with another assembly, just provide the chromosome sizes file and effective genome size as described explicitly:
-s, --chrom_sizes_file <FILE>: chromosome names and sizes.--effective_genome_size <BASES>: effective genome size, only required if using RPGC normalization.
For example:
rocco \
-i sample1.bam sample2.bam sample3.bam \
-s assemblyName.chrom.sizes \
--effective_genome_size <BASES> \
-o consensus_peaks.bed
When troubleshooting, consider processing a subset of the genome for faster evaluation:
rocco \
-i sample1.bam sample2.bam sample3.bam \
-g hg38 \
-o consensus_peaks.bed \
--chroms chr11 chr20 chr21 chr22 # at least four chroms
Example
Call consensus peaks from three BAM files and generate both narrowPeak and gappedPeak outputs:
rocco \
-i sample1.bam sample2.bam sample3.bam \
-g hg38 \
-o consensus_peaks.bed \
--peak_mode both
Paper/Citation
If using ROCCO in your research, please cite the original paper in Bioinformatics (DOI: btad725)
Nolan H Hamilton, Terrence S Furey, ROCCO: a robust method for detection of open chromatin via convex optimization,
Bioinformatics, Volume 39, Issue 12, December 2023
Installation
PyPI (pip)
python -m pip install rocco --upgrade
If lacking administrative control, you may need to append --user to the above.
Build from Source
If preferred, ROCCO can easily be built from source:
-
Clone or download this repository
git clone https://github.com/nolan-h-hamilton/ROCCO.git cd ROCCO python setup.py sdist bdist_wheel python -m pip install -e .
1 maintainer
Metadata
1 maintainer
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