Genome-wide estimation of signals hidden in noisy multi-sample HTS datasets
Reason this release was yanked:
unstable release candidate
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.
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}
}
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