{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:55:56Z","timestamp":1785545756564,"version":"3.56.0"},"reference-count":29,"publisher":"Oxford University Press (OUP)","issue":"1","license":[{"start":{"date-parts":[[2026,1,10]],"date-time":"2026-01-10T00:00:00Z","timestamp":1768003200000},"content-version":"vor","delay-in-days":4,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000054","name":"NCI","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000054","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Cancer Systems Biology Consortium","award":["U01CA243004"],"award-info":[{"award-number":["U01CA243004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,1,6]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Omics Notebook Interactive (OmNI) is an R-based, open-source, and modular framework engineered for streamlined multi-omics data integration and analysis across diverse data types, incorporating interactive visualizations at each processing step. OmNI performs differential expression analysis utilizing customizable linear models, accommodating various covariates and complex experimental designs. For cross-omic layer integration, OmNI employs a modified S-score statistic, ensuring sensitive detection of differential features. The framework also integrates network and metabolomics data, offering detailed insights into regulatory mechanisms through comprehensive enrichment analysis using multiple pathway databases. Outputs include interactive HTML reports, CSV\/TSV files, and Cytoscape-compatible objects. OmNI is readily deployable in both local and high-performance computing environments, enabling scalable data processing. Acknowledging the public health concerns of opioids, we performed TMT18-based deep proteome and phosphoproteome analysis of brains from genetically diverse collaborative cross diversity outbred (CC\/DO) founder mouse strains exposed to fentanyl to demonstrate OmNI\u2019s capabilities. The integrative S-score uniquely identified differential signaling and interaction hubs conserved across all strains and revealed strain-specific molecular neuro-responses to fentanyl. OmNI is freely available for download at https:\/\/github.com\/gracerhpotter\/OmNI\u00a0and is also accessible via a web interface at https:\/\/emili-laboratory.shinyapps.io\/omni\/.<\/jats:p>","DOI":"10.1093\/nargab\/lqaf206","type":"journal-article","created":{"date-parts":[[2025,11,28]],"date-time":"2025-11-28T13:03:21Z","timestamp":1764335001000},"source":"Crossref","is-referenced-by-count":2,"title":["OmNI: a modular open-source framework for interactive multi-omics data integration and visualization"],"prefix":"10.1093","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4591-6007","authenticated-orcid":false,"given":"Grace","family":"Potter","sequence":"first","affiliation":[{"name":"Program in Quantitative Oncology, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University , OR 97201 ,","place":["United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob 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