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However, analysis of single-molecule data is hampered by extreme yet inherent heterogeneity, making it challenging to determine the contributions of individual chromatin fibers to bulk trends. To address this challenge, we propose ChromaFactor, a novel computational approach based on non-negative matrix factorization that deconvolves single-molecule chromatin organization datasets into their most salient primary components. ChromaFactor provides the ability to identify trends accounting for the maximum variance in the dataset while simultaneously describing the contribution of individual molecules to each component. Applying our approach to two single-molecule imaging datasets across different genomic scales, we find that these primary components demonstrate significant correlation with key functional phenotypes, including active transcription, enhancer-promoter distance, and genomic compartment. Also, we find that some bulk trends exist at the single-cell level, but only in a small fraction of cells, suggesting that critical changes in genome organization may be driven by specific rare subpopulations rather than occurring uniformly across all cells. ChromaFactor offers a robust tool for understanding the complex interplay between chromatin structure and function on individual DNA molecules, pinpointing which subpopulations drive functional changes and fostering new insights into cellular heterogeneity and its implications for bulk genomic phenomena.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1012841","type":"journal-article","created":{"date-parts":[[2025,2,18]],"date-time":"2025-02-18T13:40:23Z","timestamp":1739886023000},"page":"e1012841","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":1,"title":["ChromaFactor: Deconvolution of single-molecule chromatin organization with non-negative matrix factorization"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3444-5617","authenticated-orcid":true,"given":"Laura M.","family":"Gunsalus","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1240-2192","authenticated-orcid":true,"given":"Michael J.","family":"Keiser","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9870-6196","authenticated-orcid":true,"given":"Katherine S.","family":"Pollard","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2025,2,18]]},"reference":[{"issue":"1","key":"pcbi.1012841.ref001","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.cell.2020.09.014","article-title":"The self-organizing genome: principles of genome architecture and function","volume":"183","author":"T Misteli","year":"2020","journal-title":"Cell"},{"issue":"1","key":"pcbi.1012841.ref002","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1038\/s41576-022-00526-0","article-title":"The spatial organization of transcriptional control","volume":"24","author":"A Hafner","year":"2023","journal-title":"Nat Rev Genet"},{"issue":"3","key":"pcbi.1012841.ref003","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1038\/nmeth.4155","article-title":"Massively multiplex single-cell Hi-C","volume":"14","author":"V Ramani","year":"2017","journal-title":"Nat Methods"},{"issue":"7661","key":"pcbi.1012841.ref004","doi-asserted-by":"crossref","first-page":"61","DOI":"10.1038\/nature23001","article-title":"Cell-cycle dynamics of chromosomal organization at single-cell resolution","volume":"547","author":"T Nagano","year":"2017","journal-title":"Nature"},{"issue":"7750","key":"pcbi.1012841.ref005","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1038\/s41586-019-1035-4","article-title":"Visualizing DNA folding and RNA in embryos at single-cell resolution","volume":"568","author":"LJ Mateo","year":"2019","journal-title":"Nature"},{"issue":"6","key":"pcbi.1012841.ref006","first-page":"1641-1659.e26","article-title":"Genome-scale imaging of the 3D organization and transcriptional activity of chromatin","volume":"182","author":"J-H Su","year":"2020","journal-title":"Cell"},{"issue":"1","key":"pcbi.1012841.ref007","doi-asserted-by":"crossref","first-page":"212-222.e5","DOI":"10.1016\/j.molcel.2019.01.011","article-title":"Microscopy-based chromosome conformation capture enables simultaneous visualization of genome organization and transcription in intact organisms","volume":"74","author":"AM Cardozo Gizzi","year":"2019","journal-title":"Mol Cell"},{"issue":"1","key":"pcbi.1012841.ref008","doi-asserted-by":"crossref","first-page":"2907","DOI":"10.1038\/s41467-020-16732-5","article-title":"Multiplexed imaging of nucleome architectures in single cells of mammalian tissue","volume":"11","author":"M Liu","year":"2020","journal-title":"Nat. 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