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      UpSetR: an R package for the visualization of intersecting sets and their properties

      research-article
      1 , 2 , 1
      Bioinformatics
      Oxford University Press

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          Abstract

          Motivation: Venn and Euler diagrams are a popular yet inadequate solution for quantitative visualization of set intersections. A scalable alternative to Venn and Euler diagrams for visualizing intersecting sets and their properties is needed.

          Results: We developed UpSetR, an open source R package that employs a scalable matrix-based visualization to show intersections of sets, their size, and other properties.

          Availability and implementation: UpSetR is available at https://github.com/hms-dbmi/UpSetR/ and released under the MIT License. A Shiny app is available at https://gehlenborglab.shinyapps.io/upsetr/.

          Contact: nils@ 123456hms.harvard.edu

          Supplementary information: Supplementary data are available at Bioinformatics online.

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          Most cited references6

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          Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods

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            Graphical Perception: Theory, Experimentation, and Application to the Development of Graphical Methods

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              Sets and intersections

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                Author and article information

                Journal
                Bioinformatics
                Bioinformatics
                bioinformatics
                Bioinformatics
                Oxford University Press
                1367-4803
                1367-4811
                15 September 2017
                22 June 2017
                22 June 2017
                : 33
                : 18
                : 2938-2940
                Affiliations
                [1 ]Department of Biomedical Informatics, Harvard Medical School, Boston, MA 02115, USA
                [2 ]SCI Institute, School of Computing, University of Utah, Salt Lake City, UT 84112, USA
                Author notes
                [* ]To whom correspondence should be addressed.
                [*]

                Associate Editor: John Hancock

                Article
                btx364
                10.1093/bioinformatics/btx364
                5870712
                28645171
                1c115639-23d4-4dae-bf26-2504d8e0a3d9
                © The Author 2017. Published by Oxford University Press.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 25 March 2017
                : 19 May 2017
                : 05 June 2017
                Page count
                Pages: 3
                Funding
                Funded by: National Institutes of Health 10.13039/100000002
                Award ID: R00HG007583
                Award ID: U54HG007963
                Award ID: U01CA198935
                Categories
                Applications Notes
                Genome Analysis

                Bioinformatics & Computational biology
                Bioinformatics & Computational biology

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