Figures & Supplementary Materials

A paper’s figures are often the first thing reviewers look at — and the last thing authors polish. Clear, publication-quality figures with precise captions can mean the difference between “accept with minor revisions” and “major revisions required.” AI can help generate, refine, and caption your visual elements while you ensure they accurately represent your science.

🔄 Quick Recall: In the previous lesson, you drafted your manuscript with AI assistance — introduction through discussion. Now you’ll create the visual elements that complement your text: figures, tables, captions, and supplementary materials.

Publication-Quality Figure Standards

Every journal has specific requirements, but universal standards apply.

AI-Assisted Figure Creation

Data Visualization Prompt

Create a publication-quality figure for:

Data: [describe your data — variables, groups, N]
Message: [what should the reader see immediately?]
Figure type: [scatter, bar, violin, heatmap, etc.]
Target journal: [name — for style matching]

Requirements:
- Individual data points visible (if N < 50)
- Error bars: [SE / SD / 95% CI] — specify which
- Significance markers: [*, **, *** with threshold definitions]
- Colorblind-safe palette
- Clean, minimal design (no gridlines, no chartjunk)
- Axis labels with units
- Font size: minimum 8pt when printed at column width

Figure type decision guide:

✅ Quick Check: You have pre- and post-treatment data for 20 patients. Which figure best shows the treatment effect? (Answer: A paired dot plot — dots for each patient connected by lines. This shows both the group trend and individual variation. Some patients might improve while others worsen, and this figure makes that visible. A bar chart of means would hide individual responses entirely.)

Writing Figure Captions

The caption makes a figure self-explanatory. AI can draft captions, but you must verify every detail.

Write a publication-quality caption for this figure:

Figure shows: [what's being displayed]
X-axis: [variable, units]
Y-axis: [variable, units]
Groups: [what each bar/line/color represents]
N: [sample size per group]
Error bars represent: [SE / SD / 95% CI]
Statistical test: [which test, correction if any]
Significance levels: [*, **, *** thresholds]
Key finding: [what the reader should notice]

Format: "Figure N. [Title sentence.] [Methods/details.] [Statistics.]"

Caption checklist:

• What was measured (not just “Results”)
• Sample sizes for each group
• What error bars represent (SE, SD, or CI)
• Statistical test used
• Significance thresholds defined
• Any abbreviations defined
• Scale bars for microscopy images
• Color/symbol legend (if not in figure)

Table Design

Tables complement figures — they show exact values where figures show patterns.

Format this data as a publication-quality table:

Data: [your data]
Key comparisons: [what the reader should compare]
Target journal style: [AMA, APA, journal-specific]

Rules:
- No vertical lines (most journals)
- Horizontal lines: top, bottom, and under headers only
- Align decimal points in numerical columns
- Include units in column headers, not in cells
- Footnotes for significance markers and abbreviations
- Bold or highlight key comparisons (if journal allows)

✅ Quick Check: Should you present the same data in both a figure and a table? (Answer: Generally no — pick one. Figures show patterns and trends; tables show exact values. If a reviewer needs precise numbers from your figure, a supplementary table is appropriate. But duplicating the same data in both a figure and a table wastes space and may annoy reviewers who see it as padding.)

Supplementary Materials Organization

Help me organize supplementary materials for my paper:

Main text figures: [list with brief descriptions]
Additional figures not in main text: [list]
Additional tables not in main text: [list]
Extended methods: [any procedures too detailed for main Methods]
Raw data or code: [what you're depositing]
Additional analyses: [sensitivity analyses, robustness checks]

Create:
1. Supplementary table of contents
2. Numbering scheme (Figures S1-SN, Tables S1-SN)
3. Order matching main text reference sequence
4. Cross-reference guide (which main text section references each item)
5. Caption templates for each supplementary item

What goes in supplementary vs. main text:

Practice Exercise

1. Take one figure from your current work and write a publication-quality caption using the prompt above — does it pass the “stand-alone test”?
2. Create an organization plan for your supplementary materials using the template
3. Check your figures against the journal’s specific requirements (resolution, format, color mode)

Key Takeaways

• Figures are often the first thing reviewers (and readers) look at — invest time in quality and clarity
• Show individual data points whenever possible; avoid bar charts that hide distributions
• Captions must be self-explanatory: what was measured, sample sizes, error bar type, statistical test, and significance thresholds
• Use colorblind-safe palettes — roughly 8% of male readers can’t distinguish red from green
• Supplementary materials need structure: table of contents, sequential numbering, cross-references to main text
• AI can draft captions and organize materials, but verify every number and claim matches your data

Up Next

In the next lesson, you’ll prepare for peer review and navigate the publishing process — from formatting your submission to responding to reviewer comments effectively.