ComplexHeatmap

The "ComplexHeatmap" package is a tool for visualizing patterns and relationships in high-dimensional genomic data using parallel heatmaps enhanced with sophisticated annotation graphics. Heatmaps are a popular method in bioinformatics for displaying large datasets, such as genomic data, where the color intensity represents the magnitude of some metric, such as gene expression levels.

One critical feature of the ComplexHeatmap package is its extensive customization options. Users can tailor their heatmaps to fit specific requirements, adjusting aspects like color schemes, data representation styles, and annotation methods. This level of customization is crucial for accurately interpreting complex genomic data.

Another significant capability of ComplexHeatmap is arranging multiple parallel heatmaps, which is useful when comparing or correlating different datasets or aspects of data, such as comparing gene expression under different conditions or correlating gene expression with other genomic features.

The package also allows the integration of user-defined annotation graphics. These annotations can enhance the interpretability of the heatmaps, providing contextual information that can be critical for understanding the biological significance of the patterns observed.

Topic

Data visualisation

Detail

  • Operation: Image annotation;Heat map generation

  • Software interface: Command-line user interface;Library

  • Language: R

  • License: The MIT License

  • Cost: Free

  • Version name: 2.16.0

  • Credit: The German Cancer Research Center-Heidelberg Center for Personalized Oncology, the BMBF-funded de.NBI HD-HuB network

  • Input: -

  • Output: -

  • Contact: Zuguang Gu z.gu@dkfz.de

  • Collection: -

  • Maturity: Stable

Publications

  • Complex heatmaps reveal patterns and correlations in multidimensional genomic data.
  • Gu Z, et al. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. 2016; 32:2847-9. doi: 10.1093/bioinformatics/btw313
  • https://doi.org/10.1093/bioinformatics/btw313
  • PMID: 27207943
  • PMC: -

Download and documentation


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