Building a cluster heat map using dendrograms using R

Question

I am following this example on how to create a cluster heat map with dendrograms c R plotly. Here is an example:

library(ggplot2)
library(ggdendro)
library(plotly)

#dendogram data
x <- as.matrix(scale(mtcars))
dd.col <- as.dendrogram(hclust(dist(x)))
dd.row <- as.dendrogram(hclust(dist(t(x))))
dx <- dendro_data(dd.row)
dy <- dendro_data(dd.col)

# helper function for creating dendograms
ggdend <- function(df) {
  ggplot() +
    geom_segment(data = df, aes(x=x, y=y, xend=xend, yend=yend)) +
    labs(x = "", y = "") + theme_minimal() +
    theme(axis.text = element_blank(), axis.ticks = element_blank(),
          panel.grid = element_blank())
}

# x/y dendograms
px <- ggdend(dx$segments)
py <- ggdend(dy$segments) + coord_flip()

# heatmap
col.ord <- order.dendrogram(dd.col)
row.ord <- order.dendrogram(dd.row)
xx <- scale(mtcars)[col.ord, row.ord]
xx_names <- attr(xx, "dimnames")
df <- as.data.frame(xx)
colnames(df) <- xx_names[[2]]
df$car <- xx_names[[1]]
df$car <- with(df, factor(car, levels=car, ordered=TRUE))
mdf <- reshape2::melt(df, id.vars="car")
p <- ggplot(mdf, aes(x = variable, y = car)) + geom_tile(aes(fill = value))

mat <- matrix(unlist(dplyr::select(df,-car)),nrow=nrow(df))
colnames(mat) <- colnames(df)[1:ncol(df)-1]
rownames(mat) <- rownames(df)

# hide axis ticks and grid lines
eaxis <- list(
  showticklabels = FALSE,
  showgrid = FALSE,
  zeroline = FALSE
)

p_empty <- plot_ly(filename="r-docs/dendrogram") %>%
  # note that margin applies to entire plot, so we can
  # add it here to make tick labels more readable
  layout(margin = list(l = 200),
         xaxis = eaxis,
         yaxis = eaxis)

subplot(px, p_empty, p, py, nrows = 2, margin = 0.01)

which gives:

I changed the code a bit, so in my case the heatmap is generated using plotly, rather than ggplot, because it works faster on my real big data, so I do:

heatmap.plotly <- plot_ly() %>% add_heatmap(z=~mat,x=factor(colnames(mat),lev=colnames(mat)),y=factor(rownames(mat),lev=rownames(mat)))

And then:

subplot(px, p_empty, heatmap.plotly, py, nrows = 2, margin = 0.01)

which gives:

My questions:

• How to get shortcuts for rows and columns of a heat map that will not be disabled, as in both graphs?

• The colorimeter label changes to “mat” in the second figure. Any idea how to prevent this?

• How to change the fields between thermal insulation and dendrograms?

Answer 1

, . , R, heatmaply, . -.

:

install.packages("ggplot2")
install.packages("plotly")
install.packages("heatmaply")

library(heatmaply)
heatmaply(scale(mtcars), k_row = 3, k_col = 2)

( , ). , dendextend ( ggdendro, , , // )

( ), , , .

Answer 2

, > ?

margin

sply <- subplot(px, p_empty, heatmap.plotly, py, nrows = 2)
sply <- layout(sply,
               margin = list(l = 150,
                             r = 0,
                             b = 50,
                             t = 0
                            )
               )

"" . , ?

, , .

sply$x$data[[3]]$colorbar$title <- 'mat'

?

domain . yaxis , yaxis2 ..

, .

sply <- layout(sply,
               yaxis = list(domain=c(0.47, 1)),
               xaxis = list(domain=c(0, 0.5)),
               xaxis3 = list(domain=c(0, 0.5)),
               xaxis4 = list(domain=c(0.5, 1)),
               )

---

pl <- subplot(px, p_empty, p, py, nrows = 2)
heatmap.plotly <- plot_ly() %>% add_heatmap(z=~mat,x=factor(colnames(mat),lev=colnames(mat)),y=factor(rownames(mat),lev=rownames(mat)))
sply <- subplot(px, p_empty, heatmap.plotly, py, nrows = 2)
sply$x$data[[3]]$colorbar$title <- 'mat'
sply <- layout(sply,
               yaxis = list(domain=c(0.47, 1)),
               xaxis = list(domain=c(0, 0.5)),
               xaxis3 = list(domain=c(0, 0.5)),
               xaxis4 = list(domain=c(0.5, 1)),
               margin = list(l = 150,
                             r = 0,
                             b = 50,
                             t = 0
                             )


               )

sply