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Genome-wide estimation of signals hidden in noisy multi-sample HTS datasets

Reason this release was yanked:

yanking so that the previous beta release remains the default install via pip

Project description

Consenrich

Consenrich is an adaptive linear state estimator that yields genome-wide, uncertainty-calibrated signal tracks from noisy multi-sample cohorts' epigenetic HTS data.

Simplified Schematic of Consenrich.

Special emphasis is placed on computational efficiency, model interpretability, and practical utility for downstream tasks that require well-resolved genome-wide signal estimates and uncertainty quantification across samples, such as:

  • Consensus detection of open chromatin regions, TF binding, histone modification, etc.
  • Candidate prioritization for differential analyses, functional validation, integrative modeling, etc.

See the Documentation for usage examples, installation details, configuration options, and an API reference.

Manuscript Preprint and Citation

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}
}

Project details


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