Using colors in science and color blindness

Recently we send to reviewers a paper dealing with graphs. After the first revision we realised that we should have paid some attention to the colors we use, especially because they are meant to convey information (a lot of) to any reader. One over eight people is known to suffer of some color-blind limitation and therefore it is worth to made efforts to get color-blind friendly palettes of colors (yes, it is not just a question of percentages).

This topic has been addressed in various papers Wong [2011]; Johnson and Hertig [2014]; Keene [2015]; Stauffer et al. [2015]; Nuez et al. [2018] and we refer to those papers for the main issues in making a good choice of colors. There are various colorblind types, the three more diffuse ones ;being: protanopia, deuteranopia, or tritanopia Wong [2011] and we have tried to to understand how these people perceive our graphics.
As Rudis et al. [2018] says graphs and drawing must be ”spanning as wide a palette as possible so as to make differences easy to see, perceptually uniform, meaning that values close to each other have similar-appearing colors and values far away ;from each other have more different-appearing colors, consistently across the range of values; robust to colorblindness, so that the above properties hold true for people with common forms of colorblindness, as well as in grey scale printing ..”,
To understand how colors appear to color-blind people, or to our dog, we can use the information in other website, for instance the one by Martin Krizywinsky.
But I suppose you want to use some desktop based software to do your representations. We have a little choice here. I used the web-based software by David Nichols, which can be found here. R-software users can use the VIRIDIS package but also observe that the popular ggplot2 has its own dedicated palettes. I also know for experience that Python matplotlib already does concerned default choices in this field, as apparent from the central figure of this post. Java programmers can browse Contrast-Finder. Finally if you wants just to do-it-yourself, you can read this stack-overflow thread.
If you are interested to maps, you can give a look here.

Now you cannot escape the necessity to do colorblind friendly drawings.

References

• Johnson, G. T., and S. Hertig (2014), A guide to the visual analysis and communication of biomolecular structural data, NATURE Reviews, Molecular Cell Biology, 15, 690?698.
• Keene, D. R. (2015), A review of color blindness for microscopists: Guidelines and tools for accommodating and coping with color vision deficiency, Microsc. Microanal., 21,
• Krizywinsky, M., Color palettes for color blindness, accessed: 2019-07-16.
• Nichols, D. (2018), Coloring for colorblindness, last accessed: 2019-07-16.
• Nuñez, J. R., C. R. Anderton, and R. S. Renslow (2018), Optimizing colormaps with consideration for color vision deficiency to enable accurate interpretation of scientific data, PLoS ONE, 13, e0199,239?14.
• Rudis, B., N. Ross, and S. Garnier (2018), The viridis color palettes, https://cran.r-project.org/web/packages/viridis/vignettes/intro-to-viridis.html, last accessed: 2019-08-30.
• Stauffer, R., G. J. Mayr, M. Dabernig, and A. Zeileis (2015), Somewhere over the rainbow: How to make effective use of colors in meteorological visualizations, Bull. Amer. Meteor. Soc., 96, 203?216.
• Wong, B. (2011), Color blindness, Nature Methods, 8, 441-441.