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README

Make Complex Heatmaps

Build Status codecov bioc bioc

Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. Here the ComplexHeatmap package provides a highly flexible way to arrange multiple heatmaps and supports various annotation graphics.

The InteractiveComplexHeatmap package can directly export static complex heatmaps into an interactive Shiny app. Have a try!

Citation

Zuguang Gu, Roland Eils and Matthias Schlesner, Complex heatmaps reveal patterns and correlations in multidimensional genomic data, Bioinformatics, 2016

Install

ComplexHeatmap is available on Bioconductor, you can install it by:

if (!requireNamespace("BiocManager", quietly=TRUE))
    install.packages("BiocManager")
BiocManager::install("ComplexHeatmap")

If you want the latest version, install it directly from GitHub:

library(devtools)
install_github("jokergoo/ComplexHeatmap")

Usage

Make a single heatmap:

Heatmap(mat, ...)

A single Heatmap with column annotations:

ha = HeatmapAnnotation(df = anno1, anno_fun = anno2, ...)
Heatmap(mat, ..., top_annotation = ha)

Make a list of heatmaps:

Heatmap(mat1, ...) + Heatmap(mat2, ...)

Make a list of heatmaps and row annotations:

ha = HeatmapAnnotation(df = anno1, anno_fun = anno2, ..., which = "row")
Heatmap(mat1, ...) + Heatmap(mat2, ...) + ha

Documentation

The full documentations are available at https://jokergoo.github.io/ComplexHeatmap-reference/book/ and the website is at https://jokergoo.github.io/ComplexHeatmap.

Blog posts

There are following blog posts focusing on specific topics:

Examples

Visualize Methylation Profile with Complex Annotations

complexheatmap_example4

Correlations between methylation, expression and other genomic features

complexheatmap_example3

Visualize Cell Heterogeneity from Single Cell RNASeq

complexheatmap_example2

Making Enhanced OncoPrint

complexheatmap_example1

UpSet plot

License

MIT @ Zuguang Gu

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