如何使用pheatmap的自定义聚类功能和指标

Question

我有以下功能

library(pheatmap)
plot_kmeans_heatmap <- function (dat=NULL, k=3, nstart=20) {
  # Data wrangling ----------------------------------------------------------
  set.seed(1)

  dat_m         <- kmeans(dat, k, nstart = nstart)
  m.kmeans      <- cbind(dat, dat_m$cluster)
  clusterid_col <- dim(m.kmeans)[2]


  # Ordering matrix ----------------------------------------------------------------

  # order the data row index according the last column (i.e. cluster ID)
  ordered_idx   <- order(m.kmeans[,clusterid_col])
  # order the matrix according to the order of the last column
  m.kmeans<- m.kmeans[ordered_idx,]


  # Plot it -----------------------------------------------------------------

  # Annotate row with class 
  annot_row <- m.kmeans %>% 
               transmute(gene_class=paste0("C", `dat_m$cluster`), rn=row.names(.))
  rownames(annot_row) <- annot_row$rn
  annot_row$rn <- NULL

  pheatmap(m.kmeans[,1:clusterid_col-1], 
           scale="row",
           cluster_rows=F, 
           cluster_cols=F,
           legend=T, 
           annotation_row = annot_row,
           border_color = F,
           show_rownames=F,
           show_colnames=T)

}

使用以下代码：

irisn  <- iris[sample(nrow(iris), 30), ]
dat    <- irisn[,1:4]
plot_kmeans_heatmap(dat=dat, k=6, nstart=1)

它产生了这个情节：

我的问题是，我不想使用K-means，而是想使用我自己的自定义功能：

  hclustfun = function(x) hclust(x, method='ward.D2')
  distfun = function(x) as.dist(1-cor(x, method='pearson'))

如何在pheatmap中包含它？