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chrom-seek 🔬

An awesome set of epigenetic pipelines
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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's documentation! This guide is the main source of documentation for users who are getting started with our bulk epigenetic pipelines.

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 remote reference files locally.

chrom-seek cache
Cache remote software containers locally.

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.

Contribute

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

Citation

If you use this software, please cite it as below: 

@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}
}

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

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.

Last update: 2024-11-22
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