consenrich 0.1.1b0

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 reproducible, spatially-resolved, epigenomic signals hidden in noisy multisample HTS data. The corresponding manuscript preprint is available on $$\text{bio}\textcolor{#960018}{R}\chi \text{iv}$$.

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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)

• Output:

  • Genome-wide 'consensus' epigenomic state estimates and uncertainty metrics (BedGraph/BigWig)

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Features

• Uncertainty-moderated signal tracks encompassing multiple samples' epigenomic profiles $\implies$ Insightful data representation for conventional analyses aiming to profile trait-specific regulatory landscapes (e.g., via consensus peak calling)

• Models trends and noise profiles for each sample with scale-invariance $\implies$ Multi-sample, multi-assay estimation of target molecular states from related functional genomics assays, e.g., ChIP-seq + CUT-N-RUN, ATAC-seq + DNase-seq.

• Preservation of spectral content $\implies$ Comparison and profiling of group-specific structural signatures discarded by traditional enrichment-focused measures for HTS data.

Example Use

• Run Consenrich on ten heterogeneous ATAC-seq sample alignments in the current directory (*.bam).

  consenrich --bam_files *.bam -g hg38 --signal_bigwig demo_signal.bw --residuals_bigwig demo_residuals.bw
  

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• Use Consenrich for ChIP-seq enrichment analysis with treatment/control sample alignments (POL2RA, six donors' colon tissue samples). Generate separate BigWig output tracks for signal estimates and inverse-variance weighted residuals. Use fixed-width genomic intervals of 25bp:

  consenrich \
   --bam_files \
     ENCSR322JEO_POL2RA.bam \
     ENCSR472VBD_POL2RA.bam \
     ENCSR431EHE_POL2RA.bam \
     ENCSR724FCJ_POL2RA.bam \
     ENCSR974HQI_POL2RA.bam \
     ENCSR132XRW_POL2RA.bam \
   --control_files \
     ENCSR322JEO_CTRL.bam \
     ENCSR472VBD_CTRL.bam \
     ENCSR431EHE_CTRL.bam \
     ENCSR724FCJ_CTRL.bam \
     ENCSR974HQI_CTRL.bam \
     ENCSR132XRW_CTRL.bam \
   -g hg38 --step 25 \
   -o Consenrich_POL2RA.tsv \
   --signal_bigwig Consenrich_POL2RA_CTRL_Signal.bw \
   --residual_bigwig Consenrich_POL2RA_CTRL_IVW_Residuals.bw
  

Output

Download/Install

Consenrich is available via PyPI/pip:

• pip install consenrich

If managing multiple Python environments, use 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

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},
}