knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The goal of tidyheatmaps
is to simplify the generation of publication-ready heatmaps from tidy data. By offering an interface to the powerful pheatmap
package, it allows for the effortless creation of intricate heatmaps with minimal code.
You can install the released version of tidyheatmaps from CRAN with:
install.packages("tidyheatmaps")
And the development version from GitHub with:
# install.packages("devtools") devtools::install_github("jbengler/tidyheatmaps")
Given a tidy data frame of gene expression data like data_exprs
, you can easily generate a customized heatmap. A detailed guide to Get started as well as the Full documentation can be found on GitHub.
library(tidyheatmaps) tidyheatmap(df = data_exprs, rows = external_gene_name, columns = sample, values = expression, scale = "row", annotation_col = c(sample_type, condition, group), annotation_row = c(is_immune_gene, direction), gaps_row = direction, gaps_col = group )
tidyplots relies on a number of fantastic packages that do all the heavy lifting behind the scenes. These include dplyr, pheatmap, rlang, grDevices, tidyr, tibble and RColorBrewer.
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