Complexheatmap highlight specific rows

Here's a solution for performing both tasks:

set.seed(123)
nr1 = 4; nr2 = 8; nr3 = 6; nr = nr1 + nr2 + nr3
nc1 = 6; nc2 = 8; nc3 = 10; nc = nc1 + nc2 + nc3
mat = cbind(rbind(matrix(rnorm(nr1*nc1, mean = 1,   sd = 0.5), nr = nr1),
                  matrix(rnorm(nr2*nc1, mean = 0,   sd = 0.5), nr = nr2),
                  matrix(rnorm(nr3*nc1, mean = 0,   sd = 0.5), nr = nr3)),
            rbind(matrix(rnorm(nr1*nc2, mean = 0,   sd = 0.5), nr = nr1),
                  matrix(rnorm(nr2*nc2, mean = 1,   sd = 0.5), nr = nr2),
                  matrix(rnorm(nr3*nc2, mean = 0,   sd = 0.5), nr = nr3)),
            rbind(matrix(rnorm(nr1*nc3, mean = 0.5, sd = 0.5), nr = nr1),
                  matrix(rnorm(nr2*nc3, mean = 0.5, sd = 0.5), nr = nr2),
                  matrix(rnorm(nr3*nc3, mean = 1,   sd = 0.5), nr = nr3))
)
mat = mat[sample(nr, nr), sample(nc, nc)] # random shuffle rows and columns
rownames(mat) = paste0("row", seq_len(nr))
colnames(mat) = paste0("column", seq_len(nc))

# Rows to highlight
myRows <- c('row2', 'row7')

# Set stylings for row names and make our selected rows unique
row_idx <- which(rownames(mat) %in% myRows)
fontsizes <- rep(10, nrow(mat))
fontsizes[row_idx] <- 18
fontcolors <- rep('black', nrow(mat))
fontcolors[row_idx] <- 'red'
fontfaces <- rep('plain',nrow(mat))
fontfaces[row_idx] <- 'bold'

# Create text annotation object for displaying row names
rowAnno <- rowAnnotation(rows = anno_text(rownames(mat), gp = gpar(fontsize = fontsizes, fontface = fontfaces, col = fontcolors)))

# Create our own row dendrogram (ComplexHeatmap orders rows by mean by default)
dend <- reorder(as.dendrogram(hclust(dist(mat))), -rowMeans(mat), agglo.FUN = mean)

# Find rows in dendrogram
dend_idx <- which(order.dendrogram(dend) %in% which(rownames(mat) %in% myRows))

# Find bottom and top of each row on heatmap (x and y axes go from 0 to 1)
btm <- 1 - (dend_idx / nrow(mat))
top <- btm + (1/nrow(mat))

# Draw the heatmap using our own row clustering and text decorations
Heatmap(mat, name = "ht", cluster_rows = dend, right_annotation = rowAnno, show_row_names = FALSE)

# Add boxes around our rows
box_col <- 'black'
box_width <- 3
decorate_heatmap_body("ht", { for (i in 1:length(myRows)) {
  grid.lines(c(0, 1), c(top[i],top[i]), gp = gpar(lty = 1, lwd = box_width, col = box_col))
  grid.lines(c(0, 1), c(btm[i],btm[i]), gp = gpar(lty = 1, lwd = box_width, col = box_col))
  grid.lines(c(0, 0), c(btm[i],top[i]), gp = gpar(lty = 1, lwd = box_width, col = box_col))
  grid.lines(c(1, 1), c(btm[i],top[i]), gp = gpar(lty = 1, lwd = box_width, col = box_col))
}
})

The only solution I could find is to use the row_split parameter to put a row into it's own group.

library("ComplexHeatmap")
set.seed(123)
nr1 = 4; nr2 = 8; nr3 = 6; nr = nr1 + nr2 + nr3
nc1 = 6; nc2 = 8; nc3 = 10; nc = nc1 + nc2 + nc3
mat = cbind(rbind(matrix(rnorm(nr1*nc1, mean = 1,   sd = 0.5), nr = nr1),
              matrix(rnorm(nr2*nc1, mean = 0,   sd = 0.5), nr = nr2),
              matrix(rnorm(nr3*nc1, mean = 0,   sd = 0.5), nr = nr3)),
        rbind(matrix(rnorm(nr1*nc2, mean = 0,   sd = 0.5), nr = nr1),
              matrix(rnorm(nr2*nc2, mean = 1,   sd = 0.5), nr = nr2),
              matrix(rnorm(nr3*nc2, mean = 0,   sd = 0.5), nr = nr3)),
        rbind(matrix(rnorm(nr1*nc3, mean = 0.5, sd = 0.5), nr = nr1),
              matrix(rnorm(nr2*nc3, mean = 0.5, sd = 0.5), nr = nr2),
              matrix(rnorm(nr3*nc3, mean = 1,   sd = 0.5), nr = nr3))
)
mat = mat[sample(nr, nr), sample(nc, nc)] # random shuffle rows and columns
rownames(mat) = paste0("row", seq_len(nr))
colnames(mat) = paste0("column", seq_len(nc))

cluster_rows = hclust(dist(mat))
cluster_cols = hclust(dist(t(mat)))

# reorder the matrix according to the clustering
mat_order = mat[cluster_rows$order, cluster_cols$order]

which_row2 = which(grepl("row2", rownames(mat_order)))
split = data.frame(x = c(rep("A", which_row2 - 1),
                     "B",
                     rep("C", nrow(mat_order) - which_row2)))
Heatmap(mat_order,
    cluster_rows = FALSE,
    cluster_columns = FALSE,
    row_split = split,
    row_title = NULL)