A multi-track genome browser view that displays different types of genomic data aligned along a shared chromosomal coordinate axis. Multiple parallel horizontal tracks (gene annotations, read coverage, variants, regulatory elements) are stacked vertically, each showing a different data type at the same genomic locus. This visualization is essential for integrative genomics, enabling researchers to explore relationships between gene structure, expression, variation, and regulation in a single coordinated view.
#' anyplot.ai
#' genome-track-multi: Genome Track Viewer
#' Library: ggplot2 3.5.1 | R 4.4.1
#' Quality: 89/100 | Created: 2026-06-02
library(ggplot2)
library(ragg)
set.seed(42)
# Theme tokens (Imprint palette — theme-adaptive chrome)
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"
# Imprint categorical palette — hybrid-v3 sort, first series always #009E73
IMPRINT_PALETTE <- c(
"#009E73", # 1 brand green
"#C475FD", # 2 lavender
"#4467A3", # 3 blue
"#BD8233", # 4 ochre
"#AE3030", # 5 matte red
"#2ABCCD", # 6 cyan
"#954477", # 7 rose
"#99B314" # 8 lime
)
# Genomic region: chr12: 1,000,000 – 1,100,000 (100 kb window)
CHR <- "chr12"
REGION_START <- 1000000L
REGION_END <- 1100000L
TRACK_LEVELS <- c("Genes", "Coverage", "Variants", "Regulatory")
# --- Genes track data -------------------------------------------------------
# Two genes: RAPH1 (+ strand, 3 exons) and KRAS2 (− strand, 2 exons)
exons_df <- data.frame(
xmin = c(1010000, 1025000, 1045000, 1070000, 1082000),
xmax = c(1018000, 1035000, 1060000, 1078000, 1095000),
ymin = 0.25,
ymax = 0.75,
gene = c("RAPH1 (+)", "RAPH1 (+)", "RAPH1 (+)", "KRAS2 (−)", "KRAS2 (−)"),
track = factor("Genes", levels = TRACK_LEVELS),
stringsAsFactors = FALSE
)
gene_bodies <- data.frame(
x = c(1010000, 1070000),
xend = c(1060000, 1095000),
y = 0.5,
yend = 0.5,
track = factor("Genes", levels = TRACK_LEVELS)
)
gene_labels <- data.frame(
x = c(1034000, 1082500),
y = 0.92,
label = c("RAPH1", "KRAS2"),
track = factor("Genes", levels = TRACK_LEVELS),
stringsAsFactors = FALSE
)
# --- Coverage track data ----------------------------------------------------
cov_pos <- seq(REGION_START, REGION_END, by = 500)
n_cov <- length(cov_pos)
base_cov <- 80 + 35 * sin((cov_pos - REGION_START) /
(REGION_END - REGION_START) * pi * 2.5)
# Elevated depth over exonic regions (transcribed segments)
exon_boost <- numeric(n_cov)
exon_coords <- list(
c(1010000, 1018000), c(1025000, 1035000), c(1045000, 1060000),
c(1070000, 1078000), c(1082000, 1095000)
)
for (coords in exon_coords) {
idx <- cov_pos >= coords[1] & cov_pos <= coords[2]
exon_boost[idx] <- exon_boost[idx] + rnorm(sum(idx), mean = 90, sd = 20)
}
coverage_df <- data.frame(
position = cov_pos,
depth = pmax(3, base_cov + exon_boost + rnorm(n_cov, 0, 8)),
track = factor("Coverage", levels = TRACK_LEVELS)
)
# --- Variants track data ----------------------------------------------------
variants_df <- data.frame(
position = c(1013000, 1016500, 1028000, 1031500, 1039000,
1052000, 1057500, 1071000, 1084500, 1089000, 1093000),
quality = c(55, 90, 40, 75, 30, 88, 62, 46, 95, 72, 50),
type = c("SNP", "SNP", "Indel", "SNP", "SNP",
"SNP", "Indel", "SNP", "SNP", "SNP", "Indel"),
track = factor("Variants", levels = TRACK_LEVELS),
stringsAsFactors = FALSE
)
# --- Regulatory track data --------------------------------------------------
reg_df <- data.frame(
xmin = c(1006000, 1022000, 1067000),
xmax = c(1011000, 1027000, 1072500),
ymin = 0.15,
ymax = 0.85,
element_type = c("Promoter", "Enhancer", "Promoter"),
track = factor("Regulatory", levels = TRACK_LEVELS),
stringsAsFactors = FALSE
)
reg_labels <- data.frame(
x = (reg_df$xmin + reg_df$xmax) / 2,
y = 0.50,
label = reg_df$element_type,
track = reg_df$track,
stringsAsFactors = FALSE
)
# x-range anchors ensure all 4 facets share the same genomic coordinate range
x_anchor <- data.frame(
position = rep(c(REGION_START, REGION_END), 4),
y_dummy = 0,
track = factor(rep(TRACK_LEVELS, each = 2), levels = TRACK_LEVELS)
)
# --- Plot -------------------------------------------------------------------
p <- ggplot() +
geom_blank(data = x_anchor, aes(x = position, y = y_dummy)) +
# Genes: intron connector lines, then exon rectangles, then gene name labels
geom_segment(
data = gene_bodies,
aes(x = x, xend = xend, y = y, yend = yend),
color = INK_SOFT, linewidth = 0.5
) +
geom_rect(
data = exons_df,
aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = gene),
color = NA
) +
geom_text(
data = gene_labels,
aes(x = x, y = y, label = label),
color = INK, size = 3.0, fontface = "italic"
) +
# Coverage: filled area chart of read depth
geom_area(
data = coverage_df,
aes(x = position, y = depth),
fill = IMPRINT_PALETTE[3],
alpha = 0.65,
color = IMPRINT_PALETTE[3],
linewidth = 0.25
) +
# Variants: lollipop chart (stem + head) coloured by variant type
geom_segment(
data = variants_df,
aes(x = position, xend = position, y = 0, yend = quality, color = type),
linewidth = 0.7
) +
geom_point(
data = variants_df,
aes(x = position, y = quality, color = type),
size = 2.8
) +
# Regulatory elements: coloured rectangles with label text
geom_rect(
data = reg_df,
aes(xmin = xmin, xmax = xmax, ymin = ymin, ymax = ymax, fill = element_type),
alpha = 0.85, color = NA
) +
geom_text(
data = reg_labels,
aes(x = x, y = y, label = label),
color = INK, size = 2.2, fontface = "bold"
) +
facet_grid(track ~ ., scales = "free_y", space = "fixed") +
scale_x_continuous(
name = paste(CHR, "position (Mb)"),
labels = function(x) sprintf("%.3f", x / 1e6),
expand = c(0.02, 0)
) +
scale_y_continuous(name = NULL, breaks = NULL) +
# Imprint fill scale: gene strands + regulatory element types
scale_fill_manual(
name = NULL,
values = c(
"RAPH1 (+)" = IMPRINT_PALETTE[1],
"KRAS2 (−)" = IMPRINT_PALETTE[2],
"Promoter" = IMPRINT_PALETTE[5],
"Enhancer" = IMPRINT_PALETTE[6]
)
) +
# Imprint color scale: variant types
scale_color_manual(
name = "Variant",
values = c(
"SNP" = IMPRINT_PALETTE[4],
"Indel" = IMPRINT_PALETTE[7]
)
) +
labs(title = "genome-track-multi · r · ggplot2 · anyplot.ai") +
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.major.y = element_line(color = INK_MUTED, linewidth = 0.15),
panel.grid.minor = element_blank(),
panel.border = element_rect(color = INK_SOFT, fill = NA, linewidth = 0.4),
panel.spacing = unit(0.15, "lines"),
axis.title.x = element_text(color = INK, size = 10,
margin = margin(t = 6)),
axis.text.x = element_text(color = INK_SOFT, size = 8),
axis.text.y = element_blank(),
axis.ticks.y = element_blank(),
plot.title = element_text(color = INK, size = 12, face = "plain",
margin = margin(b = 10)),
strip.text = element_text(color = INK, size = 9, face = "bold",
hjust = 0, margin = margin(l = 4, r = 4)),
strip.background = element_rect(fill = ELEVATED_BG, color = INK_SOFT,
linewidth = 0.4),
legend.background = element_rect(fill = ELEVATED_BG, color = INK_SOFT,
linewidth = 0.4),
legend.text = element_text(color = INK_SOFT, size = 8),
legend.title = element_text(color = INK, size = 9),
legend.position = "bottom",
legend.key.size = unit(0.4, "cm"),
plot.margin = margin(12, 12, 8, 8)
)
# --- Save -------------------------------------------------------------------
ggsave(
filename = sprintf("plot-%s.png", THEME),
plot = p,
device = ragg::agg_png,
width = 8,
height = 4.5,
units = "in",
dpi = 400
)
Runnable source as JSON, for any HTTP client: https://api.anyplot.ai/specs/genome-track-multi/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": "genome-track-multi",
"language": "r",
"library": "ggplot2",
"page": "https://anyplot.ai/genome-track-multi/r/ggplot2",
"hub": "https://anyplot.ai/genome-track-multi",
"code_json": "https://api.anyplot.ai/specs/genome-track-multi/ggplot2/code",
"spec_json": "https://api.anyplot.ai/specs/genome-track-multi",
"render_light_png": "https://storage.googleapis.com/anyplot-images/plots/genome-track-multi/r/ggplot2/plot-light.png",
"render_dark_png": "https://storage.googleapis.com/anyplot-images/plots/genome-track-multi/r/ggplot2/plot-dark.png",
"quality_score": 89.0,
"license": "MIT",
"guide": "https://anyplot.ai/llms.txt"
}Part of Genome Track Viewer on anyplot.ai.