Hclust object from Factorminer does not cluster dendrogram in Pheatmap

Cross posted: https://www.biostars.org/p/450365/

I am trying to create a heatmap of a matrix with 20 rows and 10 columns using pheatmap::pheatmap. To cluster the columns, I am using an hclust object obtained after running FactoMineR::HCPC on the input matrix. However, when I use the hclust object, the

This is my code:

library(tidyverse)
library(pheatmap)
library(FactoMineR)

# reproducible df of 20 rows and 10 columns
set.seed(100)
tmp <- matrix(rnorm(10000), nrow = 20, ncol = 10)
tmp <- as.data.frame(tmp)
colnames(tmp) <- paste0('col_', seq(1:ncol(tmp)))
rownames(tmp) <- paste0('row_', seq(1:nrow(tmp)))

# use FactoMineR HCPC for clustering data
res.pcahcpc <- FactoMineR::PCA(X = t(tmp), graph = F)
res.pcahcpc <- FactoMineR::HCPC(res.pcahcpc, nb.clust = 4, graph = F)

# get hclust object from FactoMineR::HCPC
pcahcpc.tree <- res.pcahcpc$call$t$tree

# hclust object
> pcahcpc.tree

Call:
flashClust::hclust(d = dissi, method = method, members = weight)

Cluster method   : ward 
Distance         : euclidean 
Number of objects: 10 

# get cluster information for heatmap annotation
res.pcahcpc <- res.pcahcpc$data.clust # clusters
colnames(res.pcahcpc)[ncol(res.pcahcpc)] <- "PCA_HCPC"
res.pcahcpc <- res.pcahcpc[,'PCA_HCPC', drop = F]

# clusters
> head(res.pcahcpc)
      PCA_HCPC
col_1        1
col_2        1
col_3        4
col_4        2
col_5        3
col_6        1

# create heatmap using PCA HCPC clustering
tmp %>%
  pheatmap(cellwidth = 15, cellheight = 15,
           annotation_col = res.pcahcpc,
           cluster_cols = pcahcpc.tree)

Running the above code gives me the heatmap below which is weird because it is not clustering the columns by FactorMiner PCA HCPC at all. Can someone explain why so?

To get the correct dendrogram, you need first to reorder the columns of tmp according to the information given in pcahcpc.tree$labels.

idx <- as.numeric(gsub("col_","", pcahcpc.tree$labels))
pheatmap(tmp[, idx], cellwidth=15, cellheight=12,
         annotation_col = res.pcahcpc,
         cluster_cols = pcahcpc.tree)

The pheatmap dendogram for columns now is the same as the dendrogram given by stats:::plot.hclust

plot(pcahcpc.tree)