ROCCO: [R]obust [O]pen [C]hromatin Detection via [C]onvex [O]ptimization

ROCCO is an optimal consensus peak calling algorithm for chromatin accessibility data that is scalable to large sample sizes.

Features

1. Consideration of enrichment and spatial characteristics of open chromatin signals to capture the full extent of peaks
2. Mathematically tractable model that permits performance and efficiency guarantees
3. Efficient for large numbers of samples with an asymptotic time complexity independent of sample size
4. No arbitrary thresholds on the minimum number of supporting samples/replicates
5. No required training data or a heuristically determined set of initial candidate peak regions

Demo

A brief walkthrough with visualized peak results using publicly available ATAC-seq data:

https://github.com/nolan-h-hamilton/ROCCO/tree/main/docs/demo/demo.ipynb

Paper/Citation

If using ROCCO in your research, please cite the original paper in Bioinformatics

 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

DOI: 10.1093/bioinformatics/btad725

Documentation

ROCCO's documentation is available at https://nolan-h-hamilton.github.io/ROCCO/

Installation

pip install rocco

ROCCO utilizes the popular bioinformatics software Samtools and bedtools. If not available already, these system dependencies can be installed with standard MacOS or Linux/Unix package managers, e.g., brew install samtools (Homebrew), sudo apt-get install samtools (APT).

Input

To determine consensus peaks (BED format), ROCCO accepts BAM alignments and a genome sizes file as input

rocco -i sample1.bam sample2.bam sample3.bam [...] -g hg38.sizes --params hg38

or with a wildcard:

rocco -i *.bam -g hg38.sizes --params hg38

See rocco --help for more details.