An UpSet plot visualizes intersections of multiple sets using a matrix-based layout that scales far better than Venn diagrams beyond 3 sets. A horizontal bar chart shows individual set sizes, a dot-matrix indicates which sets participate in each intersection, and a vertical bar chart above shows the intersection cardinality. This is the modern standard for set intersection analysis, making complex overlaps between many sets immediately readable.
#' anyplot.ai
#' upset-basic: UpSet Plot for Multi-Set Intersection Analysis
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 93/100 | Created: 2026-09-09
library(ggplot2)
library(dplyr)
library(patchwork)
library(ragg)
set.seed(42)
# --- Theme tokens -------------------------------------------------------
THEME <- Sys.getenv("ANYPLOT_THEME", "light")
PAGE_BG <- if (THEME == "light") "#FAF8F1" else "#1A1A17"
ELEVATED_BG <- if (THEME == "light") "#FFFDF6" else "#242420"
INK <- if (THEME == "light") "#1A1A17" else "#F0EFE8"
INK_SOFT <- if (THEME == "light") "#4A4A44" else "#B8B7B0"
INK_MUTED <- if (THEME == "light") "#6B6A63" else "#A8A79F"
BRAND <- "#009E73" # Imprint palette position 1 — always first series
BLUE <- "#4467A3" # Imprint palette position 3 — high end of imprint_seq
# --- Data: differential-expression gene sets across genomic assays -----
# A shared "true DE signal" liability per gene correlates detection across
# assays, so genes with strong signal tend to surface in several assays at
# once — the realistic pattern that gives an UpSet plot higher-degree bars.
n_genes <- 2500
set_names_all <- c("RNA-seq", "ChIP-seq", "ATAC-seq", "Proteomics", "Methylation", "SNP-array")
set_intercepts <- c(-0.9, -1.3, -1.0, -1.7, -1.9, -2.2)
set_slopes <- c(1.7, 1.4, 1.6, 1.3, 1.2, 1.0)
liability <- rnorm(n_genes)
membership <- vapply(seq_along(set_names_all), function(i) {
rbinom(n_genes, 1, plogis(set_intercepts[i] + set_slopes[i] * liability))
}, integer(n_genes))
colnames(membership) <- set_names_all
membership <- membership[rowSums(membership) > 0, ]
combo_key <- apply(membership, 1, function(row) paste(set_names_all[row == 1], collapse = "|"))
intersections <- tibble(combo = combo_key) %>%
count(combo, name = "size") %>%
arrange(desc(size)) %>%
slice_head(n = 15) %>%
mutate(
intersection_id = row_number(),
degree = sapply(strsplit(combo, "\\|"), length)
)
n_int <- nrow(intersections)
member_sets <- strsplit(intersections$combo, "\\|")
set_sizes <- tibble(set = set_names_all, size = colSums(membership)) %>%
arrange(desc(size))
set_order <- set_sizes$set
set_sizes$set <- factor(set_sizes$set, levels = rev(set_order))
matrix_df <- expand.grid(
intersection_id = intersections$intersection_id,
set = set_names_all,
stringsAsFactors = FALSE
) %>%
as_tibble() %>%
rowwise() %>%
mutate(member = set %in% member_sets[[intersection_id]]) %>%
ungroup() %>%
left_join(intersections %>% select(intersection_id, degree), by = "intersection_id") %>%
mutate(set = factor(set, levels = rev(set_order)))
row_stripes <- tibble(set = factor(set_order, levels = rev(set_order))) %>%
mutate(y_pos = as.integer(set)) %>%
filter(y_pos %% 2 == 0)
degree_breaks <- seq(min(intersections$degree), max(intersections$degree), by = 1)
# --- Panel A: horizontal set-size bars (left) ---------------------------
p_left <- ggplot(set_sizes, aes(x = size, y = set)) +
geom_col(fill = BRAND, width = 0.65) +
scale_x_reverse(expand = expansion(mult = c(0.08, 0))) +
labs(x = "Set Size") +
theme_minimal(base_size = 8) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
panel.grid.major.y = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.x = element_line(color = INK, linewidth = 0.2),
axis.title.y = element_blank(),
axis.text.y = element_text(color = INK, size = 9, hjust = 1),
axis.ticks.y = element_blank(),
axis.title.x = element_text(color = INK, size = 10),
axis.text.x = element_text(color = INK_SOFT, size = 8),
axis.ticks.x = element_blank(),
plot.margin = margin(t = 2, r = 2, b = 6, l = 6)
)
# --- Panel B: intersection-size bars (top) ------------------------------
p_top <- ggplot(intersections, aes(x = factor(intersection_id, levels = seq_len(n_int)), y = size)) +
geom_col(fill = BRAND, width = 0.65) +
scale_y_continuous(expand = expansion(mult = c(0, 0.08))) +
labs(y = "Elements") +
theme_minimal(base_size = 8) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
panel.grid.major.x = element_blank(),
panel.grid.minor = element_blank(),
panel.grid.major.y = element_line(color = INK, linewidth = 0.2),
axis.title.x = element_blank(),
axis.text.x = element_blank(),
axis.ticks.x = element_blank(),
axis.title.y = element_text(color = INK, size = 10),
axis.text.y = element_text(color = INK_SOFT, size = 8),
axis.ticks.y = element_blank(),
plot.margin = margin(t = 6, r = 2, b = 2, l = 6)
)
# --- Panel C: dot matrix (set membership per intersection) -------------
p_matrix <- ggplot() +
geom_rect(
data = row_stripes,
aes(ymin = y_pos - 0.5, ymax = y_pos + 0.5, xmin = -Inf, xmax = Inf),
inherit.aes = FALSE, fill = ELEVATED_BG, color = NA
) +
geom_point(
data = matrix_df,
aes(x = factor(intersection_id, levels = seq_len(n_int)), y = set),
color = INK_MUTED, alpha = 0.28, size = 2.6
) +
geom_line(
data = filter(matrix_df, member),
aes(x = factor(intersection_id, levels = seq_len(n_int)), y = set, group = intersection_id, color = degree),
linewidth = 1.1
) +
geom_point(
data = filter(matrix_df, member),
aes(x = factor(intersection_id, levels = seq_len(n_int)), y = set, color = degree),
size = 3.4
) +
scale_color_gradient(low = BRAND, high = BLUE, name = "Sets combined", breaks = degree_breaks) +
scale_x_discrete(expand = expansion(add = 0.6)) +
theme_minimal(base_size = 8) +
theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
panel.background = element_rect(fill = PAGE_BG, color = NA),
panel.grid = element_blank(),
axis.title = element_blank(),
axis.text = element_blank(),
axis.ticks = element_blank(),
legend.position = "right",
legend.background = element_rect(fill = ELEVATED_BG, color = INK_SOFT),
legend.text = element_text(color = INK_SOFT, size = 8),
legend.title = element_text(color = INK, size = 9),
plot.margin = margin(t = 2, r = 6, b = 6, l = 2)
)
# --- Compose: blank corner, top bars, left bars, matrix -----------------
design <- "
#BBBBB
#BBBBB
ACCCCC
ACCCCC
ACCCCC
ACCCCC
ACCCCC
"
combined <- p_left + p_top + p_matrix +
patchwork::plot_layout(design = design) +
patchwork::plot_annotation(
title = "upset-basic · r · ggplot2 · anyplot.ai",
theme = theme(
plot.background = element_rect(fill = PAGE_BG, color = PAGE_BG),
plot.title = element_text(color = INK, size = 12, margin = margin(b = 8))
)
)
# --- Save -----------------------------------------------------------------
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = combined,
device = ragg::agg_png,
width = 8,
height = 4.5,
units = "in",
dpi = 400,
bg = PAGE_BG
)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/upset-basic/ggplot2/code. Any spec id and library id listed in llms-full.txt fit the same URL shape; every URL below is complete and callable.
{
"spec_id": "upset-basic",
"language": "r",
"library": "ggplot2",
"page": "https://anyplot.ai/upset-basic/r/ggplot2",
"hub": "https://anyplot.ai/upset-basic",
"code_json": "https://api.anyplot.ai/specs/upset-basic/ggplot2/code",
"spec_json": "https://api.anyplot.ai/specs/upset-basic",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/upset-basic/r/ggplot2/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/upset-basic/r/ggplot2/plot-dark.png",
"quality_score": 93.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of UpSet Plot for Multi-Set Intersection Analysis on anyplot.ai.