{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T00:38:59Z","timestamp":1740184739201,"version":"3.37.3"},"reference-count":30,"publisher":"Oxford University Press (OUP)","issue":"7","license":[{"start":{"date-parts":[[2019,11,29]],"date-time":"2019-11-29T00:00:00Z","timestamp":1574985600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000002","name":"US National Institutes of Health","doi-asserted-by":"crossref","award":["R01GM114267"],"award-info":[{"award-number":["R01GM114267"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,4,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Integrative analysis of genomic data that includes statistical methods in combination with visual exploration has gained widespread adoption. Many existing methods involve a combination of tools and resources: user interfaces that provide visualization of large genomic datasets, and computational environments that focus on data analyses over various subsets of a given dataset. Over the last few years, we have developed Epiviz as an integrative and interactive genomic data analysis tool that incorporates visualization tightly with state-of-the-art statistical analysis framework.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>In this article, we present Epiviz Feed, a proactive and automatic visual analytics system integrated with Epiviz that alleviates the burden of manually executing data analysis required to test biologically meaningful hypotheses. Results of interest that are proactively identified by server-side computations are listed as notifications in a feed. The feed turns genomic data analysis into a collaborative work between the analyst and the computational environment, which shortens the analysis time and allows the analyst to explore results efficiently.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title\/>\n                  <jats:p>We discuss three ways where the proposed system advances the field of genomic data analysis: (i) takes the first step of proactive data analysis by utilizing available CPU power from the server to automate the analysis process; (ii) summarizes hypothesis test results in a way that analysts can easily understand and investigate; (iii) enables filtering and grouping of analysis results for quick search. This effort provides initial work on systems that substantially expand how computational and visualization frameworks can be tightly integrated to facilitate interactive genomic data analysis.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>The source code for Epiviz Feed application is available at http:\/\/github.com\/epiviz\/epiviz_feed_polymer. The Epiviz Computational Server is available at http:\/\/github.com\/epiviz\/epiviz-feed-computation. Please refer to Epiviz documentation site for details: http:\/\/epiviz.github.io\/.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz883","type":"journal-article","created":{"date-parts":[[2019,11,28]],"date-time":"2019-11-28T12:12:37Z","timestamp":1574943157000},"page":"2195-2201","source":"Crossref","is-referenced-by-count":1,"title":["Proactive visual and statistical analysis of genomic data in Epiviz"],"prefix":"10.1093","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7542-6095","authenticated-orcid":false,"given":"Zhe","family":"Cui","sequence":"first","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Maryland , College Park, MD 20742, USA"},{"name":"Institute for Advanced Computer Studies, University of Maryland , College Park, MD 20742, USA"},{"name":"Center for Bioinformatics and Computational Biology, University of Maryland , College Park, MD 20742, USA"},{"name":"Human-Computer Interaction Laboratory, University of Maryland , College Park, MD 20742, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5855-5031","authenticated-orcid":false,"given":"Jayaram","family":"Kancherla","sequence":"additional","affiliation":[{"name":"Institute for Advanced Computer Studies, University of Maryland , College Park, MD 20742, USA"},{"name":"Center for Bioinformatics and Computational Biology, University of Maryland , College Park, MD 20742, USA"},{"name":"Department of Computer Science, University of Maryland , College Park, MD 20742, USA"}]},{"given":"Kyle W","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of Maryland , College Park, MD 20742, USA"}]},{"given":"Niklas","family":"Elmqvist","sequence":"additional","affiliation":[{"name":"Institute for Advanced Computer Studies, University of Maryland , College Park, MD 20742, USA"},{"name":"Human-Computer Interaction Laboratory, University of Maryland , College Park, MD 20742, USA"},{"name":"Department of Computer Science, University of Maryland , College Park, MD 20742, USA"},{"name":"College of Information Studies, University of Maryland , College Park, MD 20742, USA"}]},{"given":"H\u00e9ctor","family":"Corrada Bravo","sequence":"additional","affiliation":[{"name":"Institute for Advanced Computer Studies, University of Maryland , College Park, MD 20742, USA"},{"name":"Center for Bioinformatics and Computational Biology, University of Maryland , College Park, MD 20742, USA"},{"name":"Department of Computer Science, University of Maryland , College Park, MD 20742, USA"}]}],"member":"286","published-online":{"date-parts":[[2019,11,29]]},"reference":[{"key":"2023062300073338500_btz883-B1","doi-asserted-by":"crossref","first-page":"W537","DOI":"10.1093\/nar\/gky379","article-title":"The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2018 update","volume":"46","author":"Afgan","year":"2018","journal-title":"Nucleic Acids Res"},{"key":"2023062300073338500_btz883-B2","doi-asserted-by":"crossref","first-page":"S-1","DOI":"10.6004\/jnccn.2009.0079","article-title":"NCCN task force report: estrogen receptor and progesterone receptor testing in breast cancer by immunohistochemistry","volume":"7","author":"Allred","year":"2009","journal-title":"J. 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