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{funkyheatmap}:
Visualising data frames with mixed data types
{funkyheatmap} allows generating heatmap-like
visualisations for benchmark data frames. Funky heatmaps can be
fine-tuned by providing annotations of the columns and rows, which
allows assigning multiple palettes or geometries or grouping rows and
columns together in categories.
You can install funkyheatmap like so:
install.packages("funkyheatmap")You can also download {funkyheatmap} as a standalone
executable or a Nextflow
pipeline.
Let’s use the mtcars dataset as an example of what a
funky heatmap looks like.
library(funkyheatmap)
library(dplyr, warn.conflicts = FALSE)
library(tibble, warn.conflicts = FALSE)
data("mtcars")You can visualise the dataset as follows.
funky_heatmap(mtcars)
However, this plot can look so much better if you provide additional metadata for the rows and columns. See more information on how you can customise.
data <- mtcars %>%
rownames_to_column("id") %>%
arrange(desc(mpg))
column_info <- tribble(
~id, ~group, ~name, ~geom, ~palette, ~options,
"id", "", "", "text", NA, list(hjust = 0, width = 6),
"mpg", "overall", "Miles / gallon", "bar", "palette1", list(width = 4, legend = FALSE),
"cyl", "overall", "Number of cylinders", "bar", "palette2", list(width = 4, legend = FALSE),
"disp", "group1", "Displacement (cu.in.)", "funkyrect", "palette1", lst(),
"hp", "group1", "Gross horsepower", "funkyrect", "palette1", lst(),
"drat", "group1", "Rear axle ratio", "funkyrect", "palette1", lst(),
"wt", "group1", "Weight (1000 lbs)", "funkyrect", "palette1", lst(),
"qsec", "group2", "1/4 mile time", "circle", "palette2", lst(),
"vs", "group2", "Engine", "circle", "palette2", lst(),
"am", "group2", "Transmission", "circle", "palette2", lst(),
"gear", "group2", "# Forward gears", "circle", "palette2", lst(),
"carb", "group2", "# Carburetors", "circle", "palette2", lst()
)funky_heatmap(data, column_info = column_info, expand = list(xmax = 4))
The reference
documentation on funky_heatmap() details the exact
formats of each annotation object that you can pass to it.
Check out the vignette vignette("mtcars", "funkyheatmap")
for more information on how to customize this visualisation.
In vignette("dynbenchmark", "funkyheatmap")
we use funkyheatmap to regenerate the figures from Saelens et al. (2019)
doi:10.1038/s41587-019-0071-9.
We used Viash to wrap the
funkyheatmap::funky_heatmap() function as a standalone
executable and Nextflow
module.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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