Multi-Panel Figure Assembly
patchwork Basics
r
library(patchwork) p1 <- ggplot(df, aes(x, y)) + geom_point() p2 <- ggplot(df, aes(group, value)) + geom_boxplot() p3 <- ggplot(df, aes(x)) + geom_histogram() # Horizontal p1 + p2 + p3 # Vertical p1 / p2 / p3 # Mixed layouts (p1 | p2) / p3 (p1 + p2) / (p3 + p4)
Panel Labels
r
# Automatic labels
(p1 + p2 + p3) + plot_annotation(tag_levels = 'A')
# Custom labels
(p1 + p2 + p3) + plot_annotation(tag_levels = list(c('A', 'B', 'C')))
# Label styling
(p1 + p2) + plot_annotation(
tag_levels = 'A',
tag_prefix = '(',
tag_suffix = ')',
theme = theme(plot.tag = element_text(face = 'bold', size = 14))
)
Layout Control
r
# Width ratios p1 + p2 + plot_layout(widths = c(2, 1)) # Height ratios p1 / p2 + plot_layout(heights = c(1, 2)) # Complex grid layout <- " AAB AAB CCC " p1 + p2 + p3 + plot_layout(design = layout) # Fixed dimensions p1 + p2 + plot_layout(widths = unit(c(5, 3), 'cm'))
Shared Legends
r
# Collect legends
(p1 + p2 + p3) + plot_layout(guides = 'collect')
# Position at bottom
(p1 + p2) + plot_layout(guides = 'collect') &
theme(legend.position = 'bottom')
# Keep individual legends
(p1 + p2) + plot_layout(guides = 'keep')
Inset Plots
r
# Add inset
p1 + inset_element(p2, left = 0.6, bottom = 0.6, right = 1, top = 1)
# Multiple insets
p1 +
inset_element(p2, 0.6, 0.6, 1, 1) +
inset_element(p3, 0.02, 0.6, 0.4, 1)
cowplot Alternative
r
library(cowplot)
# Simple grid
plot_grid(p1, p2, p3, ncol = 3, labels = 'AUTO')
# With labels
plot_grid(p1, p2, labels = c('A', 'B'), label_size = 14)
# Relative widths
plot_grid(p1, p2, rel_widths = c(2, 1))
# Nested grids
top_row <- plot_grid(p1, p2, ncol = 2)
bottom_row <- p3
plot_grid(top_row, bottom_row, nrow = 2, labels = c('', 'C'))
Shared Axes
r
library(patchwork) # Same axis limits (p1 + p2) & xlim(0, 10) & ylim(0, 100) # Same theme (p1 + p2 + p3) & theme_minimal() # Same color scale (p1 + p2) & scale_color_viridis_d()
Empty Spaces
r
# Add blank panel p1 + plot_spacer() + p2 # With layout layout <- " AB# CCC " p1 + p2 + p3 + plot_layout(design = layout)
Titles and Captions
r
(p1 + p2 + p3) +
plot_annotation(
title = 'Main Title',
subtitle = 'Subtitle text',
caption = 'Data source: ...',
theme = theme(
plot.title = element_text(face = 'bold', size = 16),
plot.subtitle = element_text(size = 12, color = 'grey40')
)
)
Saving Multi-Panel Figures
r
# Combine and save
combined <- (p1 | p2) / (p3 | p4) +
plot_annotation(tag_levels = 'A') &
theme(plot.tag = element_text(face = 'bold'))
ggsave('figure.pdf', combined, width = 10, height = 8)
ggsave('figure.png', combined, width = 10, height = 8, dpi = 300)
# For specific journal dimensions
ggsave('figure.pdf', combined, width = 180, height = 150, units = 'mm')
Complex Publication Figure
r
# Create themed plots
theme_pub <- theme_bw(base_size = 10) +
theme(
panel.grid = element_blank(),
legend.position = 'none'
)
p_volcano <- create_volcano(res) + theme_pub + ggtitle('Volcano Plot')
p_pca <- create_pca(vsd) + theme_pub + ggtitle('PCA')
p_heatmap <- wrap_elements(pheatmap_grob)
p_boxplot <- create_boxplot(expr_df) + theme_pub + ggtitle('Expression')
# Assemble
figure <- (p_volcano | p_pca) / (p_heatmap | p_boxplot) +
plot_annotation(tag_levels = 'A') +
plot_layout(guides = 'collect') &
theme(
plot.tag = element_text(face = 'bold', size = 12),
legend.position = 'bottom'
)
ggsave('Figure1.pdf', figure, width = 180, height = 160, units = 'mm')
matplotlib GridSpec (Python)
python
import matplotlib.pyplot as plt from matplotlib.gridspec import GridSpec fig = plt.figure(figsize=(12, 8)) gs = GridSpec(2, 3, figure=fig) ax1 = fig.add_subplot(gs[0, 0]) # Top left ax2 = fig.add_subplot(gs[0, 1:]) # Top right, spans 2 columns ax3 = fig.add_subplot(gs[1, :]) # Bottom, spans all columns # Add plots to each axis ax1.plot(x, y) ax2.scatter(x, y) ax3.bar(x, y) plt.tight_layout()
matplotlib Panel Labels
python
# Add panel labels
for ax, label in zip([ax1, ax2, ax3], ['A', 'B', 'C']):
ax.text(-0.1, 1.1, label, transform=ax.transAxes,
fontsize=14, fontweight='bold', va='top')
matplotlib Subfigures
python
# matplotlib 3.4+ subfigures for complex layouts fig = plt.figure(figsize=(12, 8)) subfigs = fig.subfigures(1, 2, width_ratios=[2, 1]) axs_left = subfigs[0].subplots(2, 1) ax_right = subfigs[1].subplots(1, 1)
Publication Export
python
# Python
fig.savefig('figure1.pdf', bbox_inches='tight')
fig.savefig('figure1.png', dpi=300, bbox_inches='tight')
Related Skills
- •data-visualization/ggplot2-fundamentals - Individual plots
- •reporting/rmarkdown-reports - Figures in documents
- •differential-expression/de-visualization - DE-specific plots