consenrich 0.1.13b0

Genome-wide extraction of reproducible continuous-valued signals hidden in noisy multisample functional genomics data

Consenrich

Consenrich is a sequential genome-wide state estimator for extraction of epigenomic signals and pattern localization in noisy multisample HTS data.

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• Input:

  • $m \geq 1$ Sequence alignment files -t/--bam_files corresponding to each sample in a given HTS experiment
  • (Optional): $m_c = m$ control sample alignments, -c/--control_files, for each 'control' sample (e.g., ChIP-seq)
  • (Optional): wavelet-based template(s) to match for genome-wide pattern matching (--match_wavelet db<2,3,...>, sym<2,3,...>, haar, coif<1,2,...>, dmey)

• Output:

  • Genome-wide 'consensus' epigenomic state estimates and uncertainty metrics (BedGraph/BigWig)
  • (Optional) BED-like output of relative maxima in the response sequence (convolution) with wavelet-based template(s)

Example: Consenrich outputs given 10 input ATAC-seq samples (lymphoblastoid) consenrich --bam_files ENCFF*.bam -g hg38 --match_wavelet haar,db4

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Download/Install

Consenrich is available via PyPI/pip:

• python -m pip install consenrich

If lacking administrative privileges, running with flag --user may be necessary.

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Consenrich can also be easily downloaded and installed from source:

1. git clone https://github.com/nolan-h-hamilton/Consenrich.git
2. cd Consenrich
3. python setup.py sdist bdist_wheel
4. python -m pip install .
5. Check installation: consenrich --help

Manuscript Preprint and Citation

A corresponding manuscript preprint is available on bioRxiv.

Genome-Wide Uncertainty-Moderated Extraction of Signal Annotations from Multi-Sample Functional Genomics Data
Nolan H Hamilton, Benjamin D McMichael, Michael I Love, Terrence S Furey; doi: 10.1101/2025.02.05.636702

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BibTeX

@article {Hamilton2025
	author = {Hamilton, Nolan H and McMichael, Benjamin D and Love, Michael I and Furey, Terrence S},
	title = {Genome-Wide Uncertainty-Moderated Extraction of Signal Annotations from Multi-Sample Functional Genomics Data},
	year = {2025},
	doi = {10.1101/2025.02.05.636702},
	url = {https://www.biorxiv.org/content/10.1101/2025.02.05.636702v1},
}