The generation of cluster heatmaps is a subtle process (Gehlenborg and Wong, 2012; Weinstein, 2008), requiring the user to make many decisions along the way. The major decisions to be made deal with the data matrix and the dendrogram. The raw data often need to be transformed in order to have a meaningful and comparable scale, while an appropriate color palette should be picked. The clustering of the data requires us to decide on a distance measure between the observation, a linkage function, as well as a rotation and coloring of branches that manage to highlight interpretable clusters. Each such decision can have consequences on the patterns and interpretations that emerge. In this section, we go through some of the arguments in the function heatmaply, aiming to make it easy for the user to tune these important statistical and visual parameters. Our toy example visualizes the effect of vaccines on measles infection. The output is given in the static Figure 1, while an interactive version is available online in the Supplementary file ‘measles.html’. Both were created using: