Generating Publication-Ready Figures in R

This skill specializes in transforming ordinary ggplot2 plots into professional, publication-ready figures that meet the strict standards of top-tier journals like Nature, Science, Cell, and others.

Use this skill when the user wants to:

Convert ggplot plots to journal-style figures
Apply Nature/Science publication themes to existing plots
Create multi-panel figures with consistent styling
Export figures with proper DPI, dimensions, and formats
Match specific journal submission guidelines
Create colorblind-safe and publication-quality color schemes

What This Skill Does

When activated, this skill will:

Analyze existing ggplot code - Read and understand the current plot structure
Apply journal themes - Add publication-quality themes including:
- Proper font sizes and families
- Clean axis lines and backgrounds
- Journal-specific color palettes
- Legend positioning and styling
Optimize for submission - Ensure figures meet:
- DPI requirements (typically 300-600 DPI)
- Width/height specifications (single vs double column)
- File format requirements (TIFF, PDF, EPS)
- Color space requirements (CMYK vs RGB)
Create multi-panel figures - Combine plots using:
- patchwork for simple layouts
- cowplot for complex compositions
- Custom annotation and labeling
Export properly - Save with correct:
- Resolution (DPI)
- Dimensions (inches/cm)
- File format
- Color profile

Example User Requests That Should Trigger This Skill

"Transform this ggplot to Nature journal style"
"Make this figure publication-ready for Science"
"Create a two-column figure matching Cell format"
"Export these plots at 600 DPI for submission"
"Apply a colorblind-safe palette to my plots"
"Combine these four plots into one publication figure"
"Format my scatter plot for PNAS submission"

Journal Style Guidelines

Nature Style

Font: Arial or Helvetica
Font sizes: Axis titles 7-9 pt, axis labels 6-8 pt
Single column: 89 mm (3.5 in) width
Double column: 183 mm (7.2 in) width
Max height: 234 mm (9.2 in)
Resolution: 300-600 DPI
Formats: TIFF, PDF, EPS (vector preferred)

Science Style

Font: Arial
Font sizes: Title 9 pt, labels 7 pt
Single column: 57 mm (2.25 in) width
Double column: 114 mm (4.5 in) width
Resolution: 300-600 DPI
Formats: TIFF, PDF, EPS

Cell Press Style

Font: Arial or Helvetica
Single column: 85 mm (3.3 in) width
Double column: 178 mm (7 in) width
Resolution: 300 DPI minimum
Formats: TIFF, EPS, PDF

Theme Templates Available

`theme_nature()`

Clean, minimalist theme matching Nature journals:

No gray backgrounds
Minimal grid lines
Arial font family
Proper axis sizing

`theme_science()`

Theme for Science journal submissions:

Compact layout
Clean typography
Optimized for smaller widths

`theme_cellpress()`

Cell Press journal theme:

Professional appearance
Flexible legend placement
Publication-ready defaults

`theme_colorblind()`

Colorblind-safe palette with:

Viridis/Colorbrewer schemes
High contrast ratios
Print-friendly colors

Color Palettes

Nature-Approved Colors

# Primary colors
nature_colors <- c(
  blue = "#3B4992",
  red = "#EE0000",
  green = "#008B45",
  purple = "#631879"
)

Colorblind-Safe Scales

scale_fill_viridis()
scale_color_okabe_ito() (Okabe-Ito palette)
scale_color_viridis()

Example Workflow

User: Here's my ggplot code, make it Nature-style.

# Original plot
p <- ggplot(mtcars, aes(x = wt, y = mpg, color = factor(cyl))) +
  geom_point(size = 3)

Skill transforms to:

# Publication-ready version
p <- ggplot(mtcars, aes(x = "Weight (tons)", y = "Fuel Efficiency (mpg)",
                        color = "Cylinders")) +
  geom_point(size = 2.5, shape = 16, alpha = 0.8) +
  scale_color_nature() +
  theme_nature(base_size = 8) +
  labs(title = NULL)

# Export at correct size
ggsave("figure1.pdf", p, width = 3.5, height = 3, dpi = 300,
       device = "pdf")

Multi-Panel Figures

# Combine plots with patchwork
library(patchwork)

figure1 <- (panel_a | panel_b) / (panel_c | panel_d)

# Add panel labels
figure1 <- figure1 +
  plot_annotation(tag_levels = "A",
                  tag_suffix = ")")

# Export
ggsave("figure1.pdf", figure1, width = 7, height = 6, dpi = 300)

Tools & Packages Commonly Used

| Purpose | R Packages | |--------|------------| | Base plotting | ggplot2 | | Themes | ggplot2, cowplot, hrbrthemes | | Color palettes | viridis, RColorBrewer, scales, ggsci | | Multi-panel | patchwork, cowplot, ggpubr | | Export | ggplot2, ragg | | Fonts | extrafont, showtext | | Annotations | ggrepel, ggpp |

Common Journal Requirements

| Journal | Width (single) | Width (double) | Max Height | Min DPI | |---------|---------------|----------------|------------|---------| | Nature | 89 mm | 183 mm | 234 mm | 300 | | Science | 57 mm | 114 mm | 229 mm | 300 | | Cell | 85 mm | 178 mm | 229 mm | 300 | | PNAS | 87 mm | 178 mm | 227 mm | 300 | | PLOS ONE | 170 mm | - | 230 mm | 300 | | eLife | 183 mm | - | 244 mm | 300 |

Quick Reference

Applying a theme

p + theme_nature()           # Nature style
p + theme_science()          # Science style
p + theme_cellpress()        # Cell Press style
p + theme_colorblind()       # Colorblind-safe

Export formats

# Vector (preferred)
ggsave("figure.pdf", ... device = "pdf")
ggsave("figure.eps", ... device = "eps")

# Raster (high DPI)
ggsave("figure.tiff", ... device = "tiff", dpi = 600)
ggsave("figure.png", ... device = "png", dpi = 300)

Common fixes

Text too small: Increase base_size in theme
Legend overlap: Use theme(legend.position = "bottom")
Colors not distinct: Use scale_fill_viridis()
Fonts not rendering: Use extrafont::font_import()

Notes

Always check specific journal guidelines before submission
Vector formats (PDF/EPS) are preferred over raster
Use consistent styling across all figures in a paper
Test colorblind accessibility with colorblindr package
Keep axis labels clear and concise
Avoid redundant chart junk (backgrounds, grid lines)