Continuous chromatin state feature annotation of the human epigenome.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35451453", "kind": "science-record", "revision": 4, "content_hash": "sha256:72dd149428685b2d9e9813c45dc154c2198c9cc67b0ce1aef8235842bd227d15", "created_at": "2026-11-01T18:14:18Z", "updated_at": "2026-11-01T22:06:21Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Continuous chromatin state feature annotation of the human epigenome.", "doi": "10.1093/bioinformatics/btac283", "pmid": "35451453", "authors": ["Habib Daneshpajouh", "Bowen Chen", "Neda Shokraneh", "Shohre Masoumi", "Kay C Wiese", "Maxwell W Libbrecht"], "journal": "Bioinformatics (Oxford, England)", "year": 2022, "abstract": "MOTIVATION: Segmentation and genome annotation (SAGA) algorithms are widely used to understand genome activity and gene regulation. These methods take as input a set of sequencing-based assays of epigenomic activity, such as ChIP-seq measurements of histone modification and transcription factor binding. They output an annotation of the genome that assigns a chromatin state label to each genomic position. Existing SAGA methods have several limitations caused by the discrete annotation framework: such annotations cannot easily represent varying strengths of genomic elements, and they cannot easily represent combinatorial elements that simultaneously exhibit multiple types of activity. To remedy these limitations, we propose an annotation strategy that instead outputs a vector of chromatin state features at each position rather than a single discrete label. Continuous modeling is common in other fields, such as in topic modeling of text documents. We propose a method, epigenome-ssm-nonneg, that uses a non-negative state space model to efficiently annotate the genome with chromatin state features. We also propose several measures of the quality of a chromatin state feature annotation and we compare the performance of several alternative methods according to these quality measures.\nRESULTS: We show that chromatin state features from epigenome-ssm-nonneg are more useful for several downstream applications than both continuous and discrete alternatives, including their ability to identify expressed genes and enhancers. Therefore, we expect that these continuous chromatin state features will be valuable reference annotations to be used in visualization and downstream analysis.\nAVAILABILITY AND IMPLEMENTATION: Source code for epigenome-ssm is available at https://github.com/habibdanesh/epigenome-ssm and Zenodo (DOI: 10.5281/zenodo.6507585).\nSUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.", "claims": [{"id": "claim-method", "statement": "We developed a version of our model, epigenome-ssm-nonneg, in which the chromatin state features αg and the emission parameters Z are both constrained to be non-negative.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35451453", "locator": "sections[7] \"3.4 Non-negativity constraint\" paragraph 2", "quote": "We developed a version of our model, epigenome-ssm-nonneg, in which the chromatin state features αg and the emission parameters Z are both constrained to be non-negative."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Supplementary data are available at Bioinformatics online.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35451453", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "Supplementary data are available at Bioinformatics online."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We show that chromatin state features from epigenome-ssm-nonneg are more useful for several downstream applications than both continuous and discrete alternatives, including their ability to identify expressed genes and enhancers.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:35451453", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "We show that chromatin state features from epigenome-ssm-nonneg are more useful for several downstream applications than both continuous and discrete alternatives, including their ability to identify expressed genes and enhancers."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "We show that chromatin state features from epigenome-ssm-nonneg are more useful for several downstream applications than both continuous and discrete alternatives, including their ability to identify expressed genes and enhancers.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:35451453"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. 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