Welcome to our guide on color for science visuals! If you’re an academic lab researcher or building the next biotech/sustainability startup, you know how important clear figures and diagrams are for communicating your work. In the past we’ve covered how to choose colors for your science brand. In this post, we’ll dive into using color effectively in scientific figures, from choosing the right palette to ensuring your charts are accessible to all viewers.
Earlier this month, we hosted a webinar on why color choice matters, the classic red-green-blue defaults and their pros/cons, some fresh complementary color combos to make your figures pop, tips on contrast using shades of a single hue or dual palettes, and crucial advice on color accessibility in science diagrams. If you’d like to join us for future webinars, sign up here to stay in the loop.
Why Color Choices Matter
Color has the ability to guide the eye, highlight important data, and reinforce meaning. A well-chosen palette can make your work easier to understand and more engaging, while poor choices can hide relationships or mislead.
For example, heat maps often rely on red for high values and blue for low. These choices work because they draw on shared associations. Color is not just aesthetic, it is part of how your audience reads your results.
Move Beyond Standard RGB
Many scientific figures default to the standard red, green, and blue (RGB) palette because these primary colors are familiar, high-contrast, and built into most software. They are easy to distinguish for most viewers and often carry intuitive meaning, such as red for “high,” green for “low,” and blue as neutral or in between. This familiarity makes them a quick, almost automatic choice for differentiating data series. Yet the RGB approach has clear limitations. Its overuse can make figures look generic, and the red and green pairing poses serious accessibility issues since many people with color vision deficiencies cannot tell the two apart. Even for those without vision challenges, red and green often merge in grayscale printouts or blur together on low-contrast projectors. In short, while RGB is a convenient default, relying on it too heavily can weaken both clarity and inclusivity.
Better alternatives improve both distinctiveness and accessibility. Complementary pairs such as orange and blue or purple and yellow provide strong contrast, modern appeal, and better legibility for color-blind viewers.
Another strategy is to use monochromatic or analogous palettes built from multiple shades of one hue. For example, a gradient of deep navy, medium blue, and pale gray-blue creates separation while maintaining cohesion. If blue is an important color to use, here are 3 example palettes built around it:
Palettes can also be sampled directly from scientific imagery such as microscopy, field photography, or satellite data, ensuring the colors not only fit together visually but also connect back to the science itself.
One last tip is to avoid the rainbow palette. Although common, rainbow scales often create artificial breaks and are especially difficult for color-blind readers. A better choice is a perceptually uniform option such as viridis or cividis, which preserve contrast and remain accessible across audiences.
Design for Accessibility
Accessible design ensures that your work can be read by all audiences. Roughly 8% of men and 0.5% of women have some form of color blindness, most often red–green. Figures that rely solely on those hues risk excluding part of your audience.
Practical steps for accessibility include:
- Avoid problematic pairs: Do not use red and green alone. Safer options include orange and blue, or purple and yellow.
- Check your figures: Convert to grayscale to test visibility, or use simulators such as Color Oracle and Coblis.
- Ensure contrast: Pair light and dark shades to make differences visible in both color and grayscale. Tools such as the WebAIM Contrast Checker can confirm adequate contrast ratios.
- Add redundancy: Use line styles, markers, textures, or direct labels in addition to color. This ensures data can be distinguished even if colors overlap.
Several ready-made palettes, including Okabe–Ito and ColorBrewer’s “colorblind safe” sets, were created for scientific work with accessibility in mind. Starting with these options can save time and increase clarity. Check out our list of resources at the end of the blog!
Use Color to Emphasize What Is Important
Color can be used to guide attention and emphasize results. One effective approach is to use muted tones for most of the figure and a bold accent color to highlight the key element.
- In a bar chart, gray out all but one bar to spotlight a significant result.
- In a line graph, keep the control group neutral while using a bright color for the treatment.
- In a scatterplot, highlight outliers in a distinct color.
Selective use of color helps the reader focus on what matters most, without adding bias or unnecessary distraction. One accent color is usually enough to establish hierarchy.
Bringing It All Together
Effective color use in scientific figures depends on three principles: choosing a cohesive palette, ensuring accessibility, and emphasizing what matters most. Moving beyond the standard red, green, blue, and rainbow palettes allows you to design visuals that are both distinctive and clearer. Planning with accessibility in mind ensures your work can be understood by all viewers. Finally, strategic use of emphasis makes the story behind your data unmistakable.
At SayoStudio, we help researchers and science-driven companies bring clarity to their visuals. Look out for our upcoming downloadable guide with illustrated examples of color best practices. In the meantime, applying these strategies will make your figures not only more attractive, but more effective at communicating your science.
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