在 R 中的热图中围绕连接的单元格绘制等高线

Question

我有两个时间轴和每个单元格的测量值的数据。从这里我创建了一个热图。我还知道每个单元格的测量是否重要。

我的问题是在所有重要的单元格周围画一条等高线。如果细胞形成具有相同显着性值的簇，我需要在簇周围而不是在每个单独的细胞周围绘制轮廓。

数据格式如下：

   x_time y_time    metric signif
1       1      1 0.3422285  FALSE
2       2      1 0.6114085  FALSE
3       3      1 0.5381621  FALSE
4       4      1 0.5175120  FALSE
5       1      2 0.6997991  FALSE
6       2      2 0.3054885  FALSE
7       3      2 0.8353888   TRUE
8       4      2 0.3991566   TRUE
9       1      3 0.7522728   TRUE
10      2      3 0.5311418   TRUE
11      3      3 0.4972816   TRUE
12      4      3 0.4330033   TRUE
13      1      4 0.5157972   TRUE
14      2      4 0.6324151   TRUE
15      3      4 0.4734126   TRUE
16      4      4 0.4315119   TRUE

下面的代码生成此数据，其中测量是随机的 (dt$metrics)，而重要性是逻辑的 (dt$signif)。

# data example
dt <- data.frame(x_time=rep(seq(1, 4), 4), 
                 y_time=rep(seq(1, 4), each=4),
                 metric=(rnorm(16, 0.5, 0.2)),
                 signif=c(rep(FALSE, 6), rep(TRUE, 10)))

可以使用ggplot2的geom_tile单独生成热图

# Generate heatmap using ggplot2's geom_tile
library(ggplot2)
p <- ggplot(data = dt, aes(x = x_time, y = y_time))
p <- p + geom_tile(aes(fill = metric))

基于this question，我设法根据显着性值在每个单元格周围绘制了不同颜色的轮廓。

# Heatmap with lines around each significant cell
p <- ggplot(data = dt, aes(x = x_time, y = y_time))
p <- p + geom_tile(aes(fill = metric, color = signif), size = 2)
p <- p + scale_color_manual(values = c("black", "white"))

但是，这种方法不会通过在整个组周围绘制轮廓来将相邻的重要单元格组合在一起（在我链接到的问题中也有讨论）。

正如this question 所示，可以在指定区域周围绘制框，但我认为这不能扩展到所有可能的单元格簇。

Answer 1

此答案基于How to get contour lines around the grids in R-raster?。

library(data.table)
library(raster)

还要注意clump 需要安装igraph 包，而rasterToPolygons 中的dissolve = TRUE 需要rgeos。

# convert data.frame to data.table
# not strictly necessary, but enables use of convenient functions: dcast and rbindlist.
setDT(d)

# reshape to wide 
d2 <- dcast(d, y ~ x, value.var = "sig")

# reverse order of rows to match raster order
# remove first column
# convert to matrix and then to raster
r <- raster(as.matrix(d2[ , .SD[.N:1, -1]]),
            xmn = 0, xmx = ncol(d2) - 1, ymn = 0, ymx = ncol(d2) - 1)

# detect clumps of connected cells of the value TRUE
# convert raster to polygons
# dissolve polygons into multi-polygons
polys <- rasterToPolygons(clump(r), dissolve = TRUE)

# grab coordinates of individual polygons and convert to a data.table
# use idcol = TRUE to enable grouping of paths when plotting
d_poly <- rbindlist(lapply(polys@polygons,
                           function(x) as.data.table(x@Polygons[[1]]@coords)),
                    idcol = TRUE)

# plot an outline around each 'patch of significant values' using geom_path 
ggplot(d, aes(x = x, y = y)) +
  geom_tile(aes(fill = z)) +
  geom_path(data = d_poly, aes(x = x + 0.5, y = y + 0.5, group = .id),
            size = 2, color = "red")

---

数据：

d <- structure(list(x = c(1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L,
                          3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L),
                    y = c(1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L,
                          1L, 2L, 3L, 4L, 1L, 2L, 3L, 4L),
                    sig = c(FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE, TRUE,
                            TRUE, FALSE, FALSE, FALSE, TRUE, FALSE, FALSE, TRUE),
                    z = c(0.96, 0.76, 0.14, 0.93, 0.39, 0.06, 0.99, 0.77,
                          0.7, 0.72, 0.08, 0.94, 0.98,  0.83, 0.12, 0.42)),
               row.names = c(NA, -16L), class = "data.frame")

Answer 2

如果您要创建大量热图，这肯定会有点乏味（尽管可能可以从您的数据中创建具有必要值的数据框），但否则您可以使用geom_segments：

p + geom_segment(aes(x = .5, xend = 4.5, y = 4.5, yend = 4.5), colour = "white", size = 2) +
  geom_segment(aes(x = .5, xend = 2.5, y = 2.5, yend = 2.5), colour = "white", size = 2) +
  geom_segment(aes(x = 2.5, xend = 4.5, y = 1.5, yend = 1.5), colour = "white", size = 2) +
  geom_segment(aes(x = .5, xend = .5, y = 2.5, yend = 4.5), colour = "white", size = 2) +
  geom_segment(aes(x = 2.5, xend = 2.5, y = 1.5, yend = 2.5), colour = "white", size = 2) +
  geom_segment(aes(x = 4.5, xend = 4.5, y = 1.5, yend = 4.5), colour = "white", size = 2)