{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T20:36:43Z","timestamp":1776458203658,"version":"3.51.2"},"reference-count":6,"publisher":"Oxford University Press (OUP)","issue":"18","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,9,15]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Summary: Parallel heatmaps with carefully designed annotation graphics are powerful for efficient visualization of patterns and relationships among high dimensional genomic data. Here we present the ComplexHeatmap package that provides rich functionalities for customizing heatmaps, arranging multiple parallel heatmaps and including user-defined annotation graphics. We demonstrate the power of ComplexHeatmap to easily reveal patterns and correlations among multiple sources of information with four real-world datasets.<\/jats:p>\n               <jats:p>Availability and Implementation: The ComplexHeatmap package and documentation are freely available from the Bioconductor project: http:\/\/www.bioconductor.org\/packages\/devel\/bioc\/html\/ComplexHeatmap.html.<\/jats:p>\n               <jats:p>Contact: \u00a0m.schlesner@dkfz.de<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>","DOI":"10.1093\/bioinformatics\/btw313","type":"journal-article","created":{"date-parts":[[2016,5,24]],"date-time":"2016-05-24T22:59:24Z","timestamp":1464130764000},"page":"2847-2849","source":"Crossref","is-referenced-by-count":9083,"title":["Complex heatmaps reveal patterns and correlations in multidimensional genomic data"],"prefix":"10.1093","volume":"32","author":[{"given":"Zuguang","family":"Gu","sequence":"first","affiliation":[{"name":"1 Division of Theoretical Bioinformatics"},{"name":"2 Heidelberg Center for Personalized Oncology (DKFZ-HIPO), German Cancer Research Center (DKFZ), Heidelberg, Germany"}]},{"given":"Roland","family":"Eils","sequence":"additional","affiliation":[{"name":"1 Division of Theoretical Bioinformatics"},{"name":"2 Heidelberg Center for Personalized Oncology (DKFZ-HIPO), German Cancer Research Center (DKFZ), Heidelberg, Germany"},{"name":"3 Department for Bioinformatics and Functional Genomics, Institute for Pharmacy and Molecular Biotechnology (IPMB) and BioQuant, Heidelberg University, Heidelberg, Germany"}]},{"given":"Matthias","family":"Schlesner","sequence":"additional","affiliation":[{"name":"1 Division of Theoretical Bioinformatics"}]}],"member":"286","published-online":{"date-parts":[[2016,5,20]]},"reference":[{"key":"2023020113391930000_btw313-B1","doi-asserted-by":"crossref","first-page":"155","DOI":"10.1038\/nbt.3102","article-title":"Computational analysis of cell-to-cell heterogeneity in single-cell RNA-sequencing data reveals hidden subpopulations of cells","volume":"33","author":"Buettner","year":"2015","journal-title":"Nat. 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