Bio data visualization multipanel figures skills multipanel figures

Version Compatibility

Reference examples tested with: patchwork 1.2+ (axes='collect' requires this version, released 2024-01-05), cowplot 1.1+, ggplot2 3.5+, matplotlib 3.8+ (subfigures stable since 3.4).

Before using code patterns, verify installed versions match. If versions differ:

• R: packageVersion('<pkg>') then ?function_name
• Python: pip show <package> then help(module.function)

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Multi-Panel Figures

"Combine plots into a multi-panel figure" -> Arrange individual plots into a single composed figure with consistent sizing, shared legends/axes, and panel labels (a, b, c) in the Nature/Cell convention. The decision space: which composition library (patchwork most modern in R; matplotlib subfigures in Python), how to share legends and axes, and how to size at journal specifications.

• R: patchwork (modern; supports axes/guides collection since 1.2), cowplot (older; align_plots), gridExtra (basic grid arrange)
• Python: matplotlib.gridspec.GridSpec, fig.subfigures() (matplotlib 3.4+)

The Single Most Important Modern Insight -- Axes Collection Requires patchwork ≥ 1.2.0

patchwork 1.2.0 (released 2024-01-05) added axes = 'collect' and axis_titles = 'collect' to plot_layout(). These collect repeated axes / titles across subplots into a single shared axis label — the same way guides = 'collect' (available since patchwork 1.0) collects legends.

Without this, multi-panel figures with shared axes show redundant labels on every subplot (visually cluttered AND non-Nature compliant). Verify patchwork version is ≥ 1.2.0; older versions silently ignore the axes argument.

patchwork -- Modern R Composition

Goal: Compose 4 ggplot objects into a 2×2 panel figure with shared legend, collected axes, and bold panel labels (a, b, c, d) in upper-left of each subplot.

Approach: Combine plots with +, /, | operators; apply plot_layout(guides='collect', axes='collect') for shared elements; add plot_annotation(tag_levels='a') for Nature-style panel labels.

library(patchwork)
library(ggplot2)

p1 <- ggplot(df, aes(x, y)) + geom_point() + theme_classic()
p2 <- ggplot(df, aes(group, value)) + geom_boxplot() + theme_classic()
p3 <- ggplot(df, aes(x)) + geom_histogram() + theme_classic()
p4 <- ggplot(df, aes(x, y, color = group)) + geom_point() + theme_classic()

# 2x2 grid
fig <- (p1 + p2) / (p3 + p4) +
    plot_annotation(tag_levels = 'a',
                    theme = theme(plot.tag = element_text(face = 'bold', size = 10))) +
    plot_layout(guides = 'collect',         # share legends
                axes = 'collect',           # share axes (patchwork >= 1.2.0)
                axis_titles = 'collect')

ggsave('figure1.pdf', fig, width = 180, height = 140, units = 'mm', device = cairo_pdf)

patchwork Operators

p1 + p2                                     # side-by-side
p1 / p2                                     # vertical stack
(p1 | p2) / p3                              # mixed: top row two, bottom one
p1 + p2 + p3 + plot_layout(ncol = 3)
p1 + p2 + plot_layout(widths = c(2, 1))     # 2:1 width ratio

# Complex grid via design string
design <- "
AAB
AAB
CCC
"
p1 + p2 + p3 + plot_layout(design = design)

# Inset
p1 + inset_element(p2, left = 0.6, bottom = 0.6, right = 1, top = 1)

cowplot -- Alternative with Alignment Focus

library(cowplot)

# plot_grid is the workhorse
combined <- plot_grid(p1, p2, p3, p4,
                       ncol = 2, labels = 'AUTO',         # 'AUTO' = A, B, C, D
                       label_size = 12, label_fontface = 'bold',
                       align = 'hv',                       # align horizontally + vertically
                       rel_widths = c(1, 1), rel_heights = c(1, 1))

# Nested grids
top_row <- plot_grid(p1, p2, ncol = 2, labels = c('A', 'B'))
bottom <- plot_grid(p3, p4, ncol = 2, labels = c('C', 'D'))
combined <- plot_grid(top_row, bottom, nrow = 2, rel_heights = c(1, 1.2))

ggsave('figure.pdf', combined, width = 180, height = 140, units = 'mm', device = cairo_pdf)

cowplot is older but its alignment behavior is sometimes more reliable than patchwork on edge cases (axes-with-titles of different lengths).

matplotlib GridSpec (Python)

import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec

fig = plt.figure(figsize=(180/25.4, 120/25.4), constrained_layout=True)
gs = GridSpec(2, 3, figure=fig)

ax1 = fig.add_subplot(gs[0, 0])
ax2 = fig.add_subplot(gs[0, 1:])         # top right, spans columns 1-2
ax3 = fig.add_subplot(gs[1, :])           # bottom row, spans all columns

ax1.scatter(x, y, s=4, rasterized=True)
ax2.plot(x, y)
ax3.bar(cats, vals)

# Panel labels at (-0.15, 1.05) of each axes
for ax, lbl in zip([ax1, ax2, ax3], 'abc'):
    ax.text(-0.15, 1.05, lbl, transform=ax.transAxes,
            fontsize=10, fontweight='bold', va='top')

fig.savefig('figure.pdf', dpi=300, bbox_inches='tight')

matplotlib Subfigures

fig = plt.figure(figsize=(180/25.4, 120/25.4), constrained_layout=True)
subfigs = fig.subfigures(1, 2, width_ratios=[2, 1])

# Left subfigure has 2 stacked panels
axs_left = subfigs[0].subplots(2, 1)
axs_left[0].plot(x, y)
axs_left[1].scatter(x, y, rasterized=True)

# Right subfigure has one panel
ax_right = subfigs[1].subplots(1, 1)
ax_right.imshow(matrix)
subfigs[1].colorbar(ax_right.images[0], ax=ax_right, shrink=0.5)

Subfigures are stronger than GridSpec for complex compositions because each subfigure has its own constrained_layout.

Journal Sizing

Journal	Single col	Double col	Max height
Nature	89 mm	183 mm	247 mm
Cell	85 mm	174 mm	235 mm
Science	55 mm	120 mm	220 mm
PNAS	87 mm	178 mm	225 mm
eLife	86 mm	175 mm	~240 mm

Always set explicit units in mm; default inches is the most common source of "figure too large" errors.

Panel Labels — Nature/Cell Convention

• Nature: lowercase bold serif (a, b, c) in upper-left corner of each panel; 8 pt
• Cell: uppercase bold sans-serif (A, B, C); placed flush left at panel top
• Science: capital bold (A, B, C)

# patchwork tag_levels for lowercase (Nature)
plot_annotation(tag_levels = 'a',
                theme = theme(plot.tag = element_text(face = 'bold', size = 9)))
# 'A' for uppercase (Cell)
plot_annotation(tag_levels = 'A')
# 'i' for roman numerals (sometimes for sub-panels)

# cowplot
plot_grid(..., labels = 'AUTO')   # auto uppercase A, B, C
plot_grid(..., labels = 'auto')   # auto lowercase a, b, c

Per-Method Failure Modes

patchwork axes='collect' silently ignored

Trigger: Using plot_layout(axes='collect') with patchwork < 1.2.0.

Mechanism: Older versions silently accept the argument but don't act on it.

Symptom: Redundant axes on each subplot; no warning or error.

Fix: packageVersion('patchwork') must be ≥ 1.2.0. Update with install.packages('patchwork').

Default ggsave produces non-portable PDF

Trigger: ggsave('out.pdf', fig) without device = cairo_pdf.

Mechanism: Default pdf() device produces fonts that journals reject on some systems.

Symptom: Submission rejected at automated check; "non-embedded fonts."

Fix: Always device = cairo_pdf.

Figure dimensions in inches when mm intended

Trigger: ggsave('out.pdf', fig, width = 180, height = 140).

Mechanism: Default units = 'in'.

Symptom: Figure file rejected for being 180 × 140 inches.

Fix: Explicit units = 'mm'.

Panel labels not aligned to panel content

Trigger: patchwork plot_annotation(tag_levels) with subplots of different y-axis label widths.

Mechanism: Tag is positioned relative to the plot canvas, including the y-axis label area.

Symptom: Labels are at different horizontal positions in each panel.

Fix: Either standardize y-label widths (pad with whitespace) OR move tags inside the plotting area: theme(plot.tag.position = c(0.02, 0.98)).

cowplot align='v' fails on plots of different widths

Trigger: plot_grid(p_wide, p_narrow, align = 'v').

Mechanism: Vertical alignment requires same x-axis widths.

Symptom: Plots align at the y-axis but x-axis labels are offset.

Fix: Use align = 'hv' if both alignments needed; otherwise patchwork's axes='collect' handles this more gracefully.

Shared legend lost in patchwork

Trigger: (p1 + p2) + plot_layout(guides = 'collect') but p1 and p2 use different scales.

Mechanism: guides='collect' merges identical guides; different scales produce duplicate (not merged) legends.

Symptom: Two legends still appear.

Fix: Standardize the scales across subplots (same scale_color_manual(values=...)); OR drop one legend via & theme(legend.position = 'none') on the redundant plot.

matplotlib GridSpec with constrained_layout=False

Trigger: Older code with plt.subplots no constrained_layout; tight_layout fails on colorbars.

Mechanism: tight_layout doesn't know about post-hoc colorbars.

Symptom: Colorbar overlaps adjacent subplot.

Fix: plt.figure(constrained_layout=True) and use fig.add_subplot(gs[...]). constrained_layout is the default-on choice in matplotlib 3.6+.

Reconciliation

Pattern	Cause	Action
patchwork and cowplot align differently	Different alignment algorithms	Try both; cowplot's align='hv' and patchwork's axes='collect' rarely produce identical results
Panel labels position differs between sessions	Different y-axis label widths	Standardize across panels
Shared legend duplicated	Scales differ across subplots	Use identical scales OR drop legend from N-1 panels

Quantitative Thresholds

Threshold	Value	Source
Nature single column	89 mm	Nature figure guidelines
Nature double column	183 mm	Nature figure guidelines
Body text size	5-7 pt	Nature rejects outside range
Panel label size	8 pt bold	Nature convention
patchwork axes='collect' minimum version	1.2.0 (2024-01-05)	patchwork release notes

Common Errors

Error / symptom	Cause	Solution
Redundant axis labels per panel	patchwork < 1.2.0 OR axes='collect' not set	Update + add to plot_layout
Non-embedded font rejection	Default ggsave device	device = cairo_pdf
Figure 180 in × 140 in	Default units = 'in'	units = 'mm'
Panel tags misaligned	Different y-label widths	Standardize or move tag inside
Cowplot vertical alignment fails	Different x-axis widths	Use 'hv' OR switch to patchwork
Two legends instead of shared	Scales differ across subplots	Unify scales
matplotlib colorbar overlaps subplot	No constrained_layout	constrained_layout=True

References

• Pedersen TL. 2024. patchwork: the composer of plots. CRAN package (v1.2.0 release notes).
• Wilke CO. 2017. cowplot: streamlined plot theme and plot annotations for ggplot2. CRAN package.
• Hunter JD. 2007. Matplotlib: A 2D graphics environment. Comput Sci Eng 9(3):90-95.

Related Skills

• data-visualization/ggplot2-fundamentals - Individual ggplot objects
• data-visualization/matplotlib-fundamentals - Python equivalent
• reporting/figure-export - DPI / format / journal-spec compliance
• data-visualization/color-palettes - Consistent palette across subpanels