r - Complexheatmap中的Bray-Curtis距离计算方法？

Question

我在 R 中使用 Complexheatmap 函数（或“热图”），想知道是否有办法使用 Bray-Curtis 方法计算列/行距离（使用 ward.D2 聚类方法），因为它不是受支持的方法在复杂热图中。不幸的是，我需要使用这个函数而不是 heatmap.2 和 pheatmap。

这是一些虚构的鱼类数量数据（我的实际数据有 47 个站点（行）和 32 个季节，但我不确定如何在这里重新创建）：

data<-matrix(rpois(30,0.9),ncol=6, nrow=5)

colnames(data) <- c("2004W", "2004D", "2005W", "2005D", "2006W", "2006D")

# I tried assigning the method this way:

d1 <- vegdist(log(data+1), method = "bray") 

d2 <- vegdist(t(log(data+1)), method = "bray")

Heatmap(data,
  row_names_side = "left",
  row_dend_side = "left",
  column_names_side = "bottom",
  row_names_gp = gpar(cex=fontsize, fontface = "bold"),
  column_names_gp = gpar(cex=0.9, fontface = "bold"),
  row_dend_width = unit(4, "cm"),
  column_dend_height = unit(3, "cm"),
  rect_gp = gpar(col = "grey"),
  column_title = "Year/Season",
  column_names_rot = 35,
  row_title = "Site",
  clustering_distance_rows = d1,
  clustering_distance_columns = d2,
  clustering_method_rows = "ward.D2",
  clustering_method_columns = "ward.D2",
  row_km = 3,
  column_km = 4
  )

Answer 1

您应该首先定义一个用于 Bray-Curtis 距离计算的函数 ( bray_dist)。
然后，你设置clustering_distance_rows=bray_dist和 clustering_distance_rows=bray_distin Heatmap。

library(vegan)
library(ComplexHeatmap)

set.seed(1234)
data <- matrix(rpois(30,0.9),ncol=6, nrow=5)
colnames(data) <- c("2004W", "2004D", "2005W", "2005D", "2006W", "2006D")
fontsize <- 8

bray_dist <- function(x) {
  vegdist(log(x+1), method = "bray")
}

Heatmap(data, row_names_side = "left", column_names_side = "bottom", 
        row_dend_side = "left", rect_gp = gpar(col = "grey"), 
        row_names_gp = gpar(cex=fontsize, fontface = "bold"), 
        column_names_gp = gpar(cex=0.9, fontface = "bold"), 
        row_dend_width = unit(4, "cm"), column_dend_height = unit(3, "cm"), 
        column_title = "Year/Season", column_names_rot = 35, row_title = "Site", 
        clustering_distance_rows = bray_dist, clustering_distance_columns = bray_dist, 
        clustering_method_rows = "ward.D2", clustering_method_columns = "ward.D2", 
        row_km = 3, column_km = 4)