Metadata-Version: 2.2
Name: consenrich
Version: 0.1.8b0
Summary: Genome-wide extraction of reproducible continuous-valued signals hidden in noisy multisample functional genomics data
Home-page: https://github.com/nolan-h-hamilton/Consenrich
Author: Nolan H. Hamilton, Benjamin D. McMichael, Michael I. Love, Terrence S. Furey
Author-email: nolan.hamilton@unc.edu, bdmcmi@ad.unc.edu, milove@email.unc.edu, tsfurey@email.unc.edu
License: MIT
Keywords: genomics,functional genomics,epigenomics,epigenetics,signal processing,data fusion,state estimator,filter,pattern matching,bioinformatics
Classifier: Development Status :: 4 - Beta
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3.9
Description-Content-Type: text/markdown
Requires-Dist: numpy>=1.23
Requires-Dist: scipy>=1.11
Requires-Dist: pandas
Requires-Dist: pysam
Requires-Dist: pybedtools
Requires-Dist: deeptools
Requires-Dist: pyBigWig
Requires-Dist: PyWavelets
Provides-Extra: dev
Requires-Dist: pytest; extra == "dev"
Requires-Dist: sphinx; extra == "dev"
Requires-Dist: twine; extra == "dev"
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# Consenrich

[![Tests](https://github.com/nolan-h-hamilton/Consenrich/actions/workflows/Tests.yml/badge.svg?event=workflow_dispatch)](https://github.com/nolan-h-hamilton/Consenrich/actions/workflows/Tests.yml)
![PyPI - Version](https://img.shields.io/pypi/v/consenrich?logo=Python&logoColor=%23FFFFFF&color=%233776AB&link=https%3A%2F%2Fpypi.org%2Fproject%2Fconsenrich%2F)

[Consenrich](https://github.com/nolan-h-hamilton/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](https://www.biorxiv.org/content/10.1101/2025.02.05.636702v1) is available on $$\text{bio}\textcolor{#960018}{R}\chi \text{iv}$$.

---

* **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)

* Refer to [**Examples**](Examples.md) for a variety of detailed usage instances.

---

**Features**

* Consenrich explicitly models dynamic signal trends and noise profiles for each sample with scale-invariance $\implies$ [Multi-sample, multi-assay estimation of target molecular states](docs/atac_dnase.png) from related functional genomics assays, e.g., ChIP-seq + CUT-N-RUN, ATAC-seq + DNase-seq.

* Consenrich yields uncertainty-moderated signal tracks that effectively encompass multiple samples' epigenomic profiles $\implies$ Insightful data representation for profiling condition-specific regulatory landscapes (e.g., via [consensus peak calling, differential analyses, etc.](docs/GRIN1.png))

* Consenrich [preserves legitimate spectral content while attenuating noise](docs/filter_comparison.png) $\implies$ Improved comparison and profiling of condition-specific structural signatures discarded by enrichment-focused measures for HTS data.

## Download/Install

Consenrich is available via [PyPI/pip](https://pypi.org/project/consenrich/):

* `python -m pip install consenrich`

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

---

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`

---

**BibTeX**

```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},
}
```
