ggsector

Load the required R packages.

library(magrittr)
library(grid)
library(ComplexHeatmap)
library(Seurat)
library(ggplot2)
library(ggsector)

Use original coordinates with `grid.polygon`

coordinates of single sector

type of percent, start = 0, r_start = 0

tmp_df <- sector_df(x = 0.5, y = 0.5, theta = 25, r = 0.4, start = 0, r_start = 0)
head(tmp_df)
#>           x         y
#> 1 0.5000000 0.5000000
#> 2 0.5000000 0.9000000
#> 3 0.5251162 0.8992107
#> 4 0.5501333 0.8968459
#> 5 0.5749525 0.8929149
#> 6 0.5994760 0.8874333
grid.newpage()
grid.polygon(
    tmp_df$x, tmp_df$y,
    vp = viewport(height = unit(1, "snpc"), width = unit(1, "snpc"))
)

type of percent, start = 50, r_start = 0.2

tmp_df <- sector_df(x = 0.5, y = 0.5, theta = 25, r = 0.4, start = 50, r_start = 0.2)
head(tmp_df)
#>           x         y
#> 1 0.5000000 0.1000000
#> 2 0.4748838 0.1007893
#> 3 0.4498667 0.1031541
#> 4 0.4250475 0.1070851
#> 5 0.4005240 0.1125667
#> 6 0.3763932 0.1195774
grid.newpage()
grid.polygon(
    tmp_df$x, tmp_df$y,
    vp = viewport(height = unit(1, "snpc"), width = unit(1, "snpc"))
)

type of degree, start = 90, r_start = 0

tmp_df <- sector_df(
    x = 0.5, y = 0.5, theta = 180, r = 0.4,
    start = 90, r_start = 0, type = "degree"
)
head(tmp_df)
#>           x         y
#> 1 0.5000000 0.5000000
#> 2 0.9000000 0.5000000
#> 3 0.8999391 0.4930190
#> 4 0.8997563 0.4860402
#> 5 0.8994518 0.4790656
#> 6 0.8990256 0.4720974
grid.newpage()
grid.polygon(
    tmp_df$x, tmp_df$y,
    vp = viewport(height = unit(1, "snpc"), width = unit(1, "snpc"))
)

type of degree, start = 180, r_start = 0.2

tmp_df <- sector_df(
    x = 0.5, y = 0.5, theta = 180, r = 0.4,
    start = 270, r_start = 0.2, type = "degree"
)
head(tmp_df)
#>           x         y
#> 1 0.1000000 0.5000000
#> 2 0.1000609 0.5069810
#> 3 0.1002437 0.5139598
#> 4 0.1005482 0.5209344
#> 5 0.1009744 0.5279026
#> 6 0.1015221 0.5348623
grid.newpage()
grid.polygon(
    tmp_df$x, tmp_df$y,
    vp = viewport(height = unit(1, "snpc"), width = unit(1, "snpc"))
)

Coordinates of Multiple Sectors

tmp_df <- sector_df_multiple(
    x = c(0.2, 0.5, 0.8),
    theta = c(25, 50, 75),
    r = 0.15,
    start = c(75, 50, 100),
    r_start = c(0, 0.05, 0.1),
    type = "percent"
)
head(tmp_df)
#>            x         y group
#> 1 0.20000000 0.5000000     1
#> 2 0.05000000 0.5000000     1
#> 3 0.05029599 0.5094186     1
#> 4 0.05118279 0.5188000     1
#> 5 0.05265691 0.5281072     1
#> 6 0.05471253 0.5373035     1
grid.newpage()
grid.polygon(
    tmp_df$x,
    tmp_df$y,
    id = tmp_df$group,
    vp = viewport(height = unit(1, "snpc"), width = unit(1, "snpc")),
    gp = gpar(
        fill = 3:1, col = 1:3
    )
)

Use ggsector with grid

sectorGrob

sectorGrob with units of “cm” and type of “degree”

grid.newpage()
gp <- sectorGrob(
    x = unit(c(3, 5, 7), "cm"),
    y = unit(c(3, 5, 7), "cm"),
    theta = c(90, 180, 270),
    r = 1,
    start = c(180, 180, 270),
    r_start = c(0.6, 0.3, 0),
    type = "degree",
    group = factor(1:3, levels = c(2, 3, 1)),
    gp = gpar(fill = c("green", "red", "blue"))
)
grid.draw(gp)

grid.sector

grid.sector with units of “npc” and type of “percent”

grid.newpage()
grid.sector(
    x = c(0.1, 0.5, 0.9),
    y = c(0.9, 0.6, 0.1),
    theta = c(25, 50, 90),
    r = .1,
    start = c(25, 50, 100),
    r_start = c(0.06, 0.03, 0),
    type = "percent",
    group = factor(1:3, levels = c(2, 3, 1)),
    gp = gpar(col = c("green", "red", "blue"), fill = 2:4),
    default.units = "npc"
)

Use ggsector with ComplexHeatmap

Prepare data

library(magrittr)
library(ComplexHeatmap)
t0 <- cor(mtcars) %>%
    set_colnames(paste("y_", colnames(.))) %>%
    set_rownames(paste("x_", rownames(.)))
mat <- abs(t0)
mat[1:5, 1:5]
#>            y_ mpg    y_ cyl   y_ disp     y_ hp   y_ drat
#> x_ mpg  1.0000000 0.8521620 0.8475514 0.7761684 0.6811719
#> x_ cyl  0.8521620 1.0000000 0.9020329 0.8324475 0.6999381
#> x_ disp 0.8475514 0.9020329 1.0000000 0.7909486 0.7102139
#> x_ hp   0.7761684 0.8324475 0.7909486 1.0000000 0.4487591
#> x_ drat 0.6811719 0.6999381 0.7102139 0.4487591 1.0000000

cell_fun + viewport

Realized by modifying the [grid::viewport()] with cell_fun, the sector can be set with a fixed width and height

set.seed(1)
Heatmap(
    mat,
    name = "vp",
    rect_gp = gpar(type = "none"),
    cell_fun = function(j, i, x, y, width, height, fill) {
        grid.rect(
            x = x, y = y, width = width, height = height,
            gp = gpar(col = "grey", fill = NA)
        )
        grid.sector(
            theta = mat[i, j] * 100,
            r = 0.5,
            start = mat[i, j] * 100 * runif(1),
            r_start = mat[i, j] * 0.49 * runif(1),
            vp = viewport(x, y, width, height),
            gp = gpar(fill = fill, col = "transparent")
        )
    },
    width = unit(.7, "snpc"),
    height = unit(.7, "snpc")
)

cell_fun + xy

Realized in the form of coordinates + radius with cell_fun.

# The default viewport locks the horizontal and vertical axes
# so that the sector does not deform, which needs to be removed here.
# The radius 'r' is half the min(length, width).
set.seed(2)
Heatmap(
    mat,
    name = "xy + r",
    rect_gp = gpar(type = "none"),
    cell_fun = function(j, i, x, y, width, height, fill) {
        grid.rect(
            x = x, y = y, width = width, height = height,
            gp = gpar(col = "grey", fill = NA)
        )
        r <- as.numeric(min(width, height)) / 2
        grid.sector(
            x,
            y,
            theta = mat[i, j] * 100,
            r = r,
            start = mat[i, j] * 100 * runif(1),
            r_start = mat[i, j] * r * 0.9 * runif(1),
            vp = NULL,
            gp = gpar(fill = fill, col = "transparent")
        )
    },
    width = unit(.7, "snpc"),
    height = unit(.7, "snpc")
)

layer_fun + xy

Realized With layer fun

# The input matrix needs to be extracted with pindex(mat, i, j)
set.seed(3)
Heatmap(
    mat,
    name = "layer",
    rect_gp = gpar(type = "none"),
    layer_fun = function(j, i, x, y, width, height, fill) {
        grid.rect(
            x = x, y = y, width = width, height = height,
            gp = gpar(col = "grey", fill = NA)
        )
        r <- as.numeric(min(width, height)) / 2
        grid.sector(
            x,
            y,
            theta = pindex(mat, i, j) * 100,
            r = r,
            start = pindex(mat, i, j) * 100 * runif(nrow(mat) * ncol(mat)),
            r_start = pindex(mat, i, j) * r * 0.9 * runif(nrow(mat) * ncol(mat)),
            vp = NULL,
            gp = gpar(fill = fill, col = "transparent")
        )
    },
    width = unit(.7, "snpc"),
    height = unit(.7, "snpc")
)

Use ggsector with ggplot2

prepare data

library(ggsector)
library(reshape2)
df <- cor(mtcars)[1:3, 1:5] %>%
    abs() %>%
    melt(varnames = c("x", "y"))

individual

The default is TRUE, mainly to control whether to draw sector by sector with a single coordinate point or to draw as a whole on the drawing board in the form of vector.
When individual = TRUE, draw one by one, the sector will not be deformed, but when there are too many sectors drawn, the overall drawing speed will be much slower.
When individual = FALSE, drawing in vector form is faster, but it needs to be used with coord_fixed() to lock the aspect ratio of the drawing board, otherwise the sector will be deformed.

ggplot(df) +
    geom_sector(aes(x, y), theta = 75, fill = 2, individual = FALSE) +
    theme_bw() +
    theme(axis.title = element_blank())
#> For better display effect, please add `coord_fixed()`

ggplot(df) +
    geom_sector(aes(x, y), theta = 75, fill = 2, individual = FALSE) +
    coord_fixed(ratio = 3 / 5) +
    theme_bw() +
    theme(axis.title = element_blank())
#> For better display effect, please add `coord_fixed()`

ggplot(df) +
    geom_sector(aes(x, y), theta = 75, fill = 2, individual = TRUE) +
    theme_bw() +
    theme(axis.title = element_blank())

theta

The sector angle parameter, used in combination with the type parameter, the type parameter defaults to “percent”.
When type = “percent”, the complete circle is a polygon composed of 100 scattered points, and theta takes a value of 0-100.
When type = “degree”, the complete circle is a polygon composed of 360 scattered points, and theta takes a value of 0-360.

ggplot(df) +
    ## type = "percent", theta = 0-100
    geom_sector(
        aes(y, x, theta = value * 100),
        type = "percent",
        color = "blue",
        individual = TRUE
    ) +
    ## type = "degree", theta = 0-360
    geom_sector(
        aes(y, x, theta = value * 360),
        type = "degree",
        color = "red",
        alpha = 0.5,
        individual = TRUE
    ) +
    theme_bw() +
    theme(axis.title = element_blank())

Careful observation reveals:

The sectors shapes in the two modes are not completely overlapped, this is because:
when type = “percent”, the circumference is 100 scattered points, and the input value will be round() to an integer of 0-100,
when type = “degree”, the circumference is 360 scattered points, and the input value will be round() to an integer of 0-360.
The more circle points, the higher the precision, but also means the slower drawing speed.

r

radius of the outer circle of the sector(0-0.5)

ggplot(df) +
    geom_sector(
        aes(y, x, theta = value * 100),
        r = rep(c(0.15, 0.3, 0.45), 5),
        fill = 2,
        individual = TRUE
    ) +
    theme_bw() +
    theme(axis.title = element_blank())

start

ggplot(df) +
    geom_sector(
        aes(y, x, theta = value * 100),
        start = rep(c(60, 40, 20), 5),
        fill = 2,
        individual = TRUE
    ) +
    theme_bw() +
    theme(axis.title = element_blank())

r_start

The starting position parameter of the fan radius, the value is between 0 and the radius length, and the default is 0, which means drawing a fan shape. If it is greater than 0, it is to draw a sector, and the following are different displays

ggplot(df) +
    geom_sector(
        aes(y, x, theta = value * 100),
        r_start = rep(c(0.15, 0.25, 0.35), 5),
        fill = 2,
        individual = TRUE
    ) +
    theme_bw() +
    theme(axis.title = element_blank())

Use ggsector with Seurat

Due to the large raw data of “pbmc”, only the code is shown here, but not run.

Readers are invited to download the data and try it out.

## Download pbmc data from
# https://cf.10xgenomics.com/samples/cell/pbmc3k/pbmc3k_filtered_gene_bc_matrices.tar.gz
pbmc.data <- Read10X(data.dir = "../filtered_gene_bc_matrices/hg19")
pbmc <- CreateSeuratObject(
    counts = pbmc.data, project = "pbmc3k",
    min.cells = 3, min.features = 200
)
pbmc <- NormalizeData(pbmc)
pbmc <- FindVariableFeatures(pbmc, selection.method = "vst", nfeatures = 2000)
pbmc <- ScaleData(pbmc, features = rownames(pbmc))
pbmc <- RunPCA(pbmc)
pbmc <- RunUMAP(pbmc, dim = 1:10)
pbmc <- FindNeighbors(pbmc, dims = 1:10)
pbmc <- FindClusters(pbmc, resolution = 0.5)
mks <- tibble::tribble(
    ~type, ~marker,
    "Naive CD4+ T", "IL7R,CCR7",
    "CD14+ Mono", "CD14,LYZ",
    "Memory CD4+", "IL7R,S100A4",
    "B", "MS4A1",
    "CD8+ T", "CD8A",
    "FCGR3A+ Mono", "FCGR3A,MS4A7",
    "NK", "GNLY,NKG7",
    "DC", "FCER1A,CST3",
    "Platelet", "PPBP",
) %>%
    tidyr::separate_rows(marker, sep = ", *") %>%
    dplyr::distinct()
# Dotplot
DotPlot(pbmc, features = unique(mks$marker)) + coord_flip()
# contrast with DotPlot
SectorPlot(pbmc, c(mks$marker, "fsdd"), features_level = unique(rev(mks$marker)))

ggsector

Pengdong Yan

2022-11-28

Use original coordinates with `grid.polygon`

coordinates of single sector

Coordinates of Multiple Sectors

Use ggsector with grid

sectorGrob

grid.sector

Use ggsector with ComplexHeatmap

Prepare data

cell_fun + viewport

cell_fun + xy

layer_fun + xy

Use ggsector with ggplot2

prepare data

individual

theta

r

start

r_start

Use ggsector with Seurat

ggsector

Pengdong Yan

2022-11-28

Use original coordinates with grid.polygon

coordinates of single sector

Coordinates of Multiple Sectors

Use ggsector with grid

sectorGrob

grid.sector

Use ggsector with ComplexHeatmap

Prepare data

cell_fun + viewport

cell_fun + xy

layer_fun + xy

Use ggsector with ggplot2

prepare data

individual

theta

r

start

r_start

Use ggsector with Seurat

Use original coordinates with `grid.polygon`