![]() A better three-color combination would be magenta/yellow/cyan. Similar color ideas apply to microscopy, but it gets a bit trickier to find suitable color combinations when there are three or four colors in one image. How to present more accessible microscopy images Also, include different shapes, lines, or symbols to represent different sample types when possible to make the differences stand out even without considering color. Avoid the use of rainbow spectrums and instead, use scales such as green/purple or a modified rainbow with no green. Similar color rules should be used when designing maps, density plots, or other kinds of data that rely on a gradient of color. ![]() The color scales on these five heatmaps are green-black-magenta, cyan-black-red, light blue-black-yellow, purple-white-orange, and blue-white-red. ![]() The first heatmap is in a green-black-red color scale and labeled “don’t do this.” The next five heatmaps are representing the same data but in color combinations that are more easily visualized by people with red/green color-blindness. Six different ways to color-code a gene expression heatmap. For example, here are some more accessible ways to color-code a heatmap: If you use black for the middle color, choose two lighter colors for the ends of the spectrum if you use white for the middle color, choose two darker colors for the ends. Historically, warm colors represent “up” and cool colors represent “down,” but that’s not a steadfast rule. When choosing colors for heatmaps that show low values, a median, and high values (such as z-score normalized gene expression), it’s best to pick two complementary colors for the ends of the scale and either white or black for the middle. You can convey most data just as well using black/white, greyscale, or a monochromatic color scale, so don’t use two colors solely to make your data “pretty. Even better, only use multiple colors when necessary. Some alternative two-tone color combinations include green/magenta, yellow/blue, and red/cyan. Not only will it be easier for everyone to interpret, but new color combinations are also just as (if not more) visually appealing as red/greed. Yes, it’s that easy! In fact, many journals now strongly encourage authors to use other color combinations in their figures. There’s a very simple solution to the problem of unreadable figures: stop using the red/green color combination. The four images below filter the original image to simulate four variations of red/green color-blindness: deuteranopia (no green cones), deuteranomaly (reduced function of green cones), protanopia (no red cones), and protanomaly (reduced function of red cones). In the top image, labeled “Wild-type photoreceptors,” actin is labeled in red, tubulin is labeled in green, and DNA stained by DAPI is in blue. For example, take a look at what a red/green heatmap might look like to people without functioning red or green cone cells:įive versions of an immunofluorescence image of two cancer cells. However, if a person has a mutation in their red or green cone cells, distinguishing these two colors becomes much more challenging. For people with normally-functioning photoreceptors, red and green provide good contrast. The red/green color combination is classic in science, most commonly used in heatmaps and fluorescence images. This means that what works to make a figure readable by one person may not work for everyone. It’s also important to note that color-blindness is different for every person many possible inherited mutations can change how the eye perceives and interprets different colors. The genetics behind inherited color blindness are quite interesting, but let’s skip to some practical steps for making your figures more readable. This means that potentially one out of 12 males and one out of 200 females who read your paper or walk past your poster can’t easily read your figures with certain color combinations. As many as 8% of males and 0.5% of females have some form of color-blindness, the most common being difficulty in perceiving the difference between the colors red and green. Why you should care about color-blindnessĬolor-blindness affects a large portion of the population. Although there are many important aspects to designing accessible figures, I want to talk specifically about making figures accessible for people with the most common visual disability: color-blindness. Scientists often fail to design figures from the perspective of our readers, particularly readers with disabilities. A sloppy scatter-plot or unconvincing immunofluorescence image can lead others to misinterpret or even mistrust your data. It’s important that people can easily and quickly understand your data. ![]() Proper data visualization is critical for presenting your scientific work in an accessible way.
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