{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T20:02:37Z","timestamp":1773345757687,"version":"3.50.1"},"reference-count":25,"publisher":"Oxford University Press (OUP)","issue":"18","license":[{"start":{"date-parts":[[2021,3,3]],"date-time":"2021-03-03T00:00:00Z","timestamp":1614729600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R01 GM121613"],"award-info":[{"award-number":["R01 GM121613"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R24 DK106766"],"award-info":[{"award-number":["R24 DK106766"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,9,29]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Summary<\/jats:title>\n                    <jats:p>Epigenetic modifications reflect key aspects of transcriptional regulation, and many epigenomic datasets have been generated under different biological contexts to provide insights into regulatory processes. However, the technical noise in epigenomic datasets and the many dimensions (features) examined make it challenging to effectively extract biologically meaningful inferences from these datasets. We developed a package that reduces noise while normalizing the epigenomic data by a novel normalization method, followed by integrative dimensional reduction by learning and assigning epigenetic states. This package, called S3V2-IDEAS, can be used to identify epigenetic states for multiple features, or identify discretized signal intensity levels and a master peak list across different cell types for a single feature. We illustrate the outputs and performance of S3V2-IDEAS using 137 epigenomics datasets from the VISION project that provides ValIdated Systematic IntegratiON of epigenomic data in hematopoiesis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Availability and implementation<\/jats:title>\n                    <jats:p>S3V2-IDEAS pipeline is freely available as open source software released under an MIT license at: https:\/\/github.com\/guanjue\/S3V2_IDEAS_ESMP.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Supplementary information<\/jats:title>\n                    <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab148","type":"journal-article","created":{"date-parts":[[2021,3,2]],"date-time":"2021-03-02T07:31:22Z","timestamp":1614670282000},"page":"3011-3013","source":"Crossref","is-referenced-by-count":12,"title":["S3V2-IDEAS: a package for normalizing, denoising and integrating epigenomic datasets across different cell types"],"prefix":"10.1093","volume":"37","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1328-7197","authenticated-orcid":false,"given":"Guanjue","family":"Xiang","sequence":"first","affiliation":[{"name":"The Bioinformatics and Genomics Program, Huck Institutes of the Life Sciences, The Pennsylvania State University , University Park, PA 16802, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Belinda M","family":"Giardine","sequence":"additional","affiliation":[{"name":"Department of Biochemistry and Molecular Biology, The Pennsylvania State University , University Park, PA 16802, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shaun","family":"Mahony","sequence":"additional","affiliation":[{"name":"Department of Biochemistry and Molecular Biology, The Pennsylvania State University , University Park, PA 16802, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yu","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Statistics, The Pennsylvania State University , University Park, PA 16802, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4084-7516","authenticated-orcid":false,"given":"Ross C","family":"Hardison","sequence":"additional","affiliation":[{"name":"Department of Biochemistry and Molecular Biology, The Pennsylvania State University , University Park, PA 16802, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2021,3,3]]},"reference":[{"key":"2023061310533247700_btab148-B1","doi-asserted-by":"crossref","first-page":"9354","DOI":"10.1038\/s41598-019-45839-z","article-title":"The ENCODE blacklist: identification of problematic regions of the genome","volume":"9","author":"Amemiya","year":"2019","journal-title":"Sci. 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