Create interactive cluster 'heatmaps' that can be saved as a stand- alone HTML file, embedded in 'R Markdown' documents or in a 'Shiny' app, and available in the 'RStudio' viewer pane. Hover the mouse pointer over a cell to show details or drag a rectangle to zoom. A 'heatmap' is a popular graphical method for visualizing high-dimensional data, in which a table of numbers are encoded as a grid of colored cells. The rows and columns of the matrix are ordered to highlight patterns and are often accompanied by 'dendrograms'. 'Heatmaps' are used in many fields for visualizing observations, correlations, missing values patterns, and more. Interactive 'heatmaps' allow the inspection of specific value by hovering the mouse over a cell, as well as zooming into a region of the 'heatmap' by dragging a rectangle around the relevant area. This work is based on the 'ggplot2' and 'plotly.js' engine. It produces similar 'heatmaps' as 'heatmap.2' or 'd3heatmap', with the advantage of speed ('plotly.js' is able to handle larger size matrix), the ability to zoom from the 'dendrogram' panes, and the placing of factor variables in the sides of the 'heatmap'.
|Author||Tal Galili [aut, cre, cph] (https://www.r-statistics.com), Alan O'Callaghan [aut] (https://github.com/Alanocallaghan), Jonathan Sidi [ctb] (https://github.com/yonicd), Yoav Benjamini [ths]|
|Maintainer||Tal Galili <email@example.com>|
|License||GPL-2 | GPL-3|
|URL||https://talgalili.github.io/heatmaply/ https://cran.r-project.org/package=heatmaply https://github.com/talgalili/heatmaply/ https://www.r-statistics.com/tag/heatmaply/|
|Package repository||View on CRAN|
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