chrom-seek 🔬

An awesome set of epigenetic pipelines

This is the home of the pipeline, chrom-seek. Its long-term goals: to accurately call and annotate peaks, to infer cell types in cell-free samples, and to boldly quantify diferential binding or accessibility like no pipeline before!

Overview

Welcome to chrom-seek! Before getting started, we highly recommend reading through chrom-seek's documentation.

The ./chrom-seek pipeline is composed of several interrelated sub-commands to set up and run the pipeline across different systems. Each of the available sub-commands performs different functions:

• chrom-seek run: Run the chrom-seek pipeline with your input files.
• chrom-seek unlock: Unlocks a previous runs output directory.
• chrom-seek install: Download reference files locally.
• chrom-seek cache: Cache remote resources locally, coming soon!

chrom-seek is an awesome set of pipelines designed specifically for cell-free ChIP-seq, bulk ChIP-seq, and bulk ATAC-seq sequencing data. It relies on technologies like Singularity¹ to maintain the highest level of reproducibility. The pipeline consists of a series of data processing and quality-control steps orchestrated by Snakemake², a flexible and scalable workflow management system, to submit jobs to a cluster.

The pipeline is compatible with data generated from Illumina short-read sequencing technologies. As input, it accepts a set of FastQ files and can be run locally on a compute instance or on-premise using a cluster. A user can define the method or mode of execution. The pipeline can submit jobs to a cluster using a job scheduler like SLURM (more coming soon!). A hybrid approach ensures the pipeline is accessible to all users.

Before getting started, we highly recommend reading through the usage section of each available sub-command.

For more information about issues or troubleshooting a problem, please check out our FAQ prior to opening an issue on Github.

Dependencies

Requires: singularity>=3.5 snakemake>=6.0

At the current moment, the pipeline uses a mixture of environment modules and docker images; however, this will be changing soon! In the very near future, the pipeline will only use docker images. With that being said, snakemake and singularity must be installed on the target system. Snakemake orchestrates the execution of each step in the pipeline. To guarantee the highest level of reproducibility, each step of the pipeline will rely on versioned images from DockerHub. Snakemake uses singularity to pull these images onto the local filesystem prior to job execution, and as so, snakemake and singularity will be the only two dependencies in the future.

Installation

Please clone this repository to your local filesystem using the following command:

# Clone Repository from Github
git clone https://github.com/OpenOmics/chrom-seek.git
# Change your working directory
cd chrom-seek/
# Add dependencies to $PATH
# Biowulf users should run
module load snakemake singularity
# Get usage information
./chrom-seek -h

Contribute

This site is a living document, created for and by members like you. chrom-seek is maintained by the members of OpenOmics and is improved by continuous feedback! We encourage you to contribute new content and make improvements to existing content via pull requests to our GitHub repository.

Cite

If you use this software, please cite our methods paper:

@BibText

@article {Jange202302003,
	author = {Moon Kyoo Jang and Tovah E Markowitz and Temesgen E Andargie and Zainab Apalara and Skyler Kuhn and Sean Agbor-Enoh},
	title = {Cell-free chromatin immunoprecipitation to detect molecular pathways in heart transplantation},
	volume = {6},
	number = {12},
	elocation-id = {e202302003},
	year = {2023},
	doi = {10.26508/lsa.202302003},
	publisher = {Life Science Alliance},
	abstract = {Existing monitoring approaches in heart transplantation lack the sensitivity to provide deep molecular assessments to guide management, or require endomyocardial biopsy, an invasive and blind procedure that lacks the precision to reliably obtain biopsy samples from diseased sites. This study examined plasma cell-free DNA chromatin immunoprecipitation sequencing (cfChIP-seq) as a noninvasive proxy to define molecular gene sets and sources of tissue injury in heart transplant patients. In healthy controls and in heart transplant patients, cfChIP-seq reliably detected housekeeping genes. cfChIP-seq identified differential gene signals of relevant immune and nonimmune molecular pathways that were predominantly down-regulated in immunosuppressed heart transplant patients compared with healthy controls. cfChIP-seq also identified cell-free DNA tissue sources. Compared with healthy controls, heart transplant patients demonstrated greater cell-free DNA from tissue types associated with heart transplant complications, including the heart, hematopoietic cells, lungs, liver, and vascular endothelium. cfChIP-seq may therefore be a reliable approach to profile dynamic assessments of molecular pathways and sources of tissue injury in heart transplant patients.},
	URL = {https://www.life-science-alliance.org/content/6/12/e202302003},
	eprint = {https://www.life-science-alliance.org/content/6/12/e202302003.full.pdf},
	journal = {Life Science Alliance}
}

@APA

Jang, M. K., Markowitz, T. E., Andargie, T. E., Apalara, Z., Kuhn, S., & Agbor-Enoh, S. (2023). Cell-free chromatin immunoprecipitation to detect molecular pathways in heart transplantation. Life Science Alliance, 6(12), e202302003. https://doi.org/10.26508/lsa.202302003 

References

<sup>1. Kurtzer GM, Sochat V, Bauer MW (2017). Singularity: Scientific containers for mobility of compute. PLoS ONE 12(5): e0177459.
2. Koster, J. and S. Rahmann (2018). "Snakemake-a scalable bioinformatics workflow engine." Bioinformatics 34(20): 3600.</sup>