heatmap_rjs: Produce an interactive heatmap.
In RJSplot: Interactive Graphs with R

Description Usage Arguments Value Author(s) See Also Examples

heatmap_rjs creates interactive heatmaps.

heatmap_rjs(data, metadata = NULL, scale = c("row", "column", "none"),
  cluster = TRUE, color = c("Reds", "Greens", "Blues", "RdBkGr", "RdWhBu"),
  na.color = "transparent", cex = 1, plot = TRUE, jupyter = FALSE, 
  dir = tempdir(), distfun = dist, hclustfun = hclust)

`data`	numeric matrix of the values to be plotted.
`metadata`	a data frame with metadata information for column features (p.e. sample phenotypes). Samples are given in rows and features in columns.
`scale`	character indicating if the values should be centered and scaled in either the row direction or the column direction, or none. The default value is "none".
`cluster`	logical value to enable (`TRUE`) or disable (`FALSE`) data clustering.
`color`	character indicating the color scale to paint values. The default value is "Blues".
`na.color`	character indicating the color to use for missing values. Transparent by default.
`cex`	number indicating the amount by which plotting text and symbols should be scaled relative to the default.
`plot`	open resulting graph in your browser.
`jupyter`	embed the graph as an iframe into a Jupyter Notebook.
`dir`	a "character" string representing the directory where the graph will be saved.
`distfun`	function used to compute the distance between rows and columns.
`hclustfun`	function used to compute the hierarchical clustering.

The function creates a folder in your computer with an HTML document named index.html which contains the graph. This file can be directly opened with your browser.

David Barrios and Carlos Prieto. Bioinformatics Service of Nucleus, University of Salamanca. See https://bioinfo.usal.es/

The ‘RJSplot’ Website: https://rjsplot.usal.es

dendrogram_rjs, densityplot_rjs, genomemap_rjs, heatmap_rjs, manhattan_rjs, network_rjs, scatterplot_rjs, symheatmap_rjs, wordcloud_rjs, boxplot_rjs, bubbles_rjs, hiveplot_rjs, piechart_rjs, barplot_rjs, tables_rjs, surface3d_rjs, scatter3d_rjs.

## Create an interactive heatmap in a temporal directory of your local machine
## Live examples on https://rjsplot.usal.es
if(interactive()){
metadata <- data.frame(phenotype1 = sample(c("yes","no"),ncol(mtcars),TRUE),
                       phenotype2 = sample(1:5,ncol(mtcars),TRUE))

heatmap_rjs(data.matrix(mtcars), metadata, scale="column")
}