Complex heatmaps reveal patterns and correlations in multidimensional genomic data

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 paralle...

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Bibliographic Details
Main Authors: Gu, Zuguang (Author) , Eils, Roland (Author) , Schlesner, Matthias (Author)
Format: Article (Journal)
Language:English
Published: 2016 May 20
In: Bioinformatics
Year: 2016, Volume: 32, Issue: 18, Pages: 2847-2849
ISSN:1367-4811
DOI:10.1093/bioinformatics/btw313
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1093/bioinformatics/btw313
Verlag, lizenzpflichtig, Volltext: https://academic.oup.com/bioinformatics/article/32/18/2847/1743594
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Author Notes:Zuguang Gu, Roland Eils and Matthias Schlesner
Description
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. - 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 - CONTACT: m.schlesnerdkfz.de - SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
Item Description:Gesehen am 26.08.2020
Physical Description:Online Resource
ISSN:1367-4811
DOI:10.1093/bioinformatics/btw313