consenrich 0.2.0b1

Genome-wide estimation of signals hidden in noisy multi-sample functional genomics dataset

Consenrich (branch: lean)

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The lean branch introduces a substantial internal refactor that positions Consenrich for a long-term, stable, API. Underlying methodology and functionality remain unchanged, but the following improvements are introduced:

• Core methodological aspects are now self-contained, allowing users greater flexibility to separate preprocessing and primary analysis for contexts that may require unique normalization techniques, transformations of data, or other preprocessing steps.

• Consistent, documented naming conventions for modules, functions, and arguments.

• Performance upgrades — Several previous bottlenecks are now rewritten in Cython, and alignment-level processing is buffered to restrict and configure memory use.

After lean is merged into main, some previous interfaces will become deprecated but remain accessible through older tagged versions of Consenrich.

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Consenrich is a sequential state estimator for extraction of genome-wide epigenetic signals in noisy, multi-sample high-throughput functional genomics datasets.

See the Documentation (branch:lean) for more details and usage examples.

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Manuscript Preprint and Citation

A manuscript preprint is available on bioRxiv.

BibTeX Citation

@article {Hamilton2025,
	author = {Hamilton, Nolan H and Huang, Yu-Chen E 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},
	publisher = {Cold Spring Harbor Laboratory},
	journal = {bioRxiv}
}

Installation

From Source

Building and installing from source is recommended to ensure compatibility across platforms and Python versions.

1. git clone --single-branch --branch lean https://github.com/nolan-h-hamilton/Consenrich.git
2. python -m pip install setuptools wheel Cython build
3. python -m build
4. python -m pip install .

From PyPI

Consenrich distributes multiple wheels on PyPI for different Python versions and platforms. To install the latest version, run:

python -m pip install consenrich

Previous Versions

To install a specific version of Consenrich, you can specify the version number in the pip install command, for example:

python -m pip install consenrich==0.1.13b1