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How to color dendrogram tags according to specific groups? (in R)

I have a number matrix in R with 24 rows and 10,000 columns. The row names of this matrix are basically the names of the files from which I read the data corresponding to each of the 24 rows. In addition, I have a separate list of factors with 24 entires, indicating the group to which 24 files belong. There are 3 groups - alcohols, hydrocarbons and esters. The names and the corresponding group to which they belong are as follows:

> MS.mz
[1] "int-354.19" "int-361.35" "int-368.35" "int-396.38" "int-408.41" "int-410.43" "int-422.43"
[8] "int-424.42" "int-436.44" "int-438.46" "int-452.00" "int-480.48" "int-648.64" "int-312.14"
[15] "int-676.68" "int-690.62" "int-704.75" "int-312.29" "int-326.09" "int-326.18" "int-326.31"
[22] "int-340.21" "int-340.32" "int-352.35"

> MS.groups
[1] Alcohol     Alcohol     Alcohol     Alcohol     Hydrocarbon Alcohol     Hydrocarbon Alcohol    
[9] Hydrocarbon Alcohol     Alcohol     Alcohol     Ester       Alcohol     Ester       Ester      
[17] Ester       Alcohol     Alcohol     Alcohol     Alcohol     Alcohol     Alcohol     Hydrocarbon
Levels: Alcohol Ester Hydrocarbon

I wanted to create a dendrogram to see how data can be grouped in a matrix. So, I used the following commands:

require(vegan)
dist.mat<-vegdist(MS.data.scaled.transposed,method="euclidean")
clust.res<-hclust(dist.mat)
plot(clust.res)

. , , , , . , ,

dendrogram r

dendrogram R, ape

. , row.names MS.groups, dendrogram.

dendextend ( https://nycdatascience.com/wp-content/uploads/2013/09/dendextend-tutorial.pdf),

enter image description here

, :

require(colorspace)
d_SIMS <- dist(firstpointsample5[,-1])
hc_SIMS <- hclust(d_SIMS)
labels(hc_SIMS)
dend_SIMS <- as.dendrogram(hc_SIMS)
SIMS_groups <- rev(levels(firstpointsample5[, 1]))
dend_SIMS <- color_branches(dend_SIMS, k = 3, groupLabels = SIMS_groups)
is.character(labels(dend_SIMS)) 
plot(dend_SIMS)
labels_colors(dend_SIMS) <- rainbow_hcl(3)[sort_levels_values(as.numeric(firstpointsample5[,1])[order.dendrogram(dend_SIMS)])]
labels(dend_SIMS) <- paste(as.character(firstpointsample5[, 1])[order.dendrogram(dend_SIMS)],"(", labels(dend_SIMS), ")", sep = "")
dend_SIMS <- hang.dendrogram(dend_SIMS, hang_height = 0.1)
dend_SIMS <- assign_values_to_leaves_nodePar(dend_SIMS, 0.5,"lab.cex")
par(mar = c(3, 3, 3, 7))
plot(dend_SIMS, main = "Clustered SIMS dataset\n (the labels give the true m/z groups)",horiz = TRUE, nodePar = list(cex = 0.007))
legend("topleft", legend = SIMS_groups, fill = rainbow_hcl(3))
+4
3

, , , color_labels, get_leaves_branches_col. cutree (, color_branches do), , ( ( branches_attr_by_labels). :

# define dendrogram object to play with:
hc <- hclust(dist(USArrests[1:5,]), "ave")
dend <- as.dendrogram(hc)

library(dendextend)
par(mfrow = c(1,2), mar = c(5,2,1,0))
dend <- dend %>%
         color_branches(k = 3) %>%
         set("branches_lwd", c(2,1,2)) %>%
         set("branches_lty", c(1,2,1))

plot(dend)

dend <- color_labels(dend, k = 3)
# The same as:
# labels_colors(dend)  <- get_leaves_branches_col(dend)
plot(dend)

enter image description here

, set, , ( ).

+6

You can try this solution, just change the "labs" to your "MS.groups" and "var", and your "MS.groups" will be converted to numeric (possibly with as.numeric). It comes from How to color the dendrogram labels of an additional factor variable in R

## The data
df <- structure(list(labs = c("a1", "a2", "a3", "a4", "a5", "a6", "a7", 
"a8", "b1", "b2", "b3", "b4", "b5", "b6", "b7"), var = c(1L, 1L, 2L,     
1L,2L, 2L, 1L, 2L, 1L, 2L, 1L, 1L, 2L, 2L, 2L), td = c(13.1, 14.5, 16.7, 
12.9, 14.9, 15.6, 13.4, 15.3, 12.8, 14.5, 14.7, 13.1, 14.9, 15.6, 14.6), 
fd = c(2L, 3L, 3L, 1L, 2L, 3L, 2L, 3L, 2L, 4L, 2L, 1L, 4L, 3L, 3L)), 
.Names = c("labs", "var", "td", "fd"), class = "data.frame", row.names = 
c(NA, -15L))

## Subset for clustering
df.nw = df[,3:4]

# Assign the labs column to a vector
labs = df$labs

d = dist(as.matrix(df.nw))                          # find distance matrix 
hc = hclust(d, method="complete")                   # apply hierarchical clustering 

## plot the dendrogram

plot(hc, hang=-0.01, cex=0.6, labels=labs, xlab="") 

## convert hclust to dendrogram 
hcd = as.dendrogram(hc)                             

## plot using dendrogram object
plot(hcd, cex=0.6)                                  

Var = df$var                                        # factor variable for colours
varCol = gsub("1","red",Var)                        # convert numbers to colours
varCol = gsub("2","blue",varCol)

# colour-code dendrogram branches by a factor 

# ... your code
colLab <- function(n) {
  if(is.leaf(n)) {
    a <- attributes(n)
    attr(n, "label") <- labs[a$label]
    attr(n, "nodePar") <- c(a$nodePar, lab.col = varCol[a$label]) 
  }
  n
}

## Coloured plot
plot(dendrapply(hcd, colLab))
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