How to make sample vs features clustering heatmap using daisy (gower) in R?

Question

I am still learning the clustering methods.

I have a dataset with mixed types: continuous, binary, categorical. I read some articles that using 'gower' is a good clustering distance for mixed type data. So I would like to try it out and make an exploratory heatmap.

But I don't know how to make a heatmap, sample vs features from the daisy function.

library(cluster)
data(agriculture)
gower_dist <- daisy(agriculture, metric = "gower")

What I got from gower_dist is a dissimilarity matrix, but how to use gower distance on a sample vs feature heatmap using pheatmap? like the heatmap in this post?

Thank you!

Answer 1

There's an option to provide the distance matrix (see ?pheatmap) :

clustering_distance_rows: distance measure used in clustering rows.
          Possible values are ‘"correlation"’ for Pearson correlation
          and all the distances supported by ‘dist’, such as
          ‘"euclidean"’, etc. If the value is none of the above it is
          assumed that a distance matrix is provided.

You can try something like:

library(cluster)
data(agriculture)
gower_samples <- as.dist(as.matrix(daisy(agriculture, metric = "gower")))
gower_features <- as.dist(as.matrix(daisy(t(agriculture), metric = "gower")))

pheatmap(agriculture,
clustering_distance_rows=gower_samples,
clustering_distance_cols=gower_features)