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If you are interested in color, explore my other color tools, Brewer palettes resources, color blindness palettes and math and an exhausting list of 10,000 color names for all those times you couldn't distinguish between tan hide, sea buckthorn, orange peel, west side, sunshade, california and pizzaz.

Designing for Color blindness

Color choices and transformations for deuteranopia and other afflictions

Here, I help you understand color blindness and describe a process by which you can make good color choices when designing for accessibility.

The opposite of color blindness is seeing all the colors and I can help you find 1,000 (or more) maximally distinct colors.

You can also delve into the mathematics behind the color blindness simulations and learn about copunctal points (the invisible color!) and lines of confusion.

Color palettes for color blindness

In this section, I cover how to make good color choices when considering audiences with color blindness.

With the exception of the 8-color palette, all palettes have been created using a process (read below) that tries to maintain perceptual luminance uniformity in color-blind space.

1 · Conservative 8-color palette for colorbliness

This 8-color palette is adapted from Nature Method's Points of View: Color blindness by Bang Wong. Note that in that original source the RGB values listed in the table did not exactly correspond to the RGB swatches—probably an RGB vs CMYK conversion mixup.

This palette is suitable for categorical color encoding—the colors do not, as a whole, have a natural order and none is substantially more salient than another.

You can download these colors as plain text list of HEX and RGB values.

An 8-color palette for color blindness. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
An 8-color palette for color blindness, adapted from Wong, B. (2011) Nature Methods 8:441. (PDF, plain text)

For more tips about designing with color blindness in mind, see Color Universal Design (CUD) — How to make figures and presentations that are friendly to people with color blindess.

2 · Using color equivalencies

To people with color blindness, some colors appear the same. This equivalence can be used to identify colors that are distinct to those with normal as well as to those with color blindness.

For a given RGB color we can simulate how it would appear to someone with color blindess and identify groups of RGB colors that appear indistinguishable in color blindness.

Color equivalencies in color blindness for protanopia, deuteranopia and tritanopia. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Many colors appear the same to people with color blindness. This chart shows the colors that are identical (rows) to those with protanopia, deuteranopia (most common) and tritanopia

These equivalencies can be used to construct color palettes—lists of colors that are distinguishable to deuteranopes and those with normal vision.

Since deuteranopia is the most common, this is the condition that I use for color selection.

The exact luminance (perceived brightness) of the simulated color varies depending on the color blindness algorithm. Each row in the squares above should look identical using any color blindness simulation (e.g. Color Oracle, Photoshop, etc) but brightness of the rows may be slightly different than shown here.

3 · 12-color palette for colorbliness

This palette maps four colors onto each of the two color dimensions in deuteranopes and four onto greyscale. This palette is very useful for designing transit and subway maps.

Color names are playful selections from my list of 10,000 color names.

You can download these colors as plain text list of HEX and RGB values.

A 12-color palette for color blindness. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
A 12 color palette for color blindness that maps onto each of the color dimensions in deuteranopes. Within each set of four, colors also have reasonably similar greyscale tones. Inset swatches show color alternatives that are indistinguishable from the main swatch for deuternopes. (PDF, plain text)

4 · 15-color palette for colorbliness

You can download these colors as plain text list of HEX and RGB values.

A 15-color palette for color blindness. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
A 15-color palette for color blindness. (PDF, plain text)

5 · 24-color palette for colorbliness

Even more color choices for color blindess, including colors that map onto greys. For these, I don't have RGB/HEX values handy.

You can download these colors as plain text list of HEX and RGB values.

15-color palettes for color blindness / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
15-color palettes designed for each of the three types of color blindness: deuteranopia, protanopia and tritanopia. Palettes are shown as they appear to someone with normal vision as well as to someone affected with each of the three types of color blindness. Each palette contains three groups of swatches, matching to two of the color channels and greys. Within each group colors in the same row map onto the same color. (PDF)

6 · The last word on color palettes for colorbliness

You can create your own color palettes using the figure below.

For a given color blindness type (e.g. deuteranopia) and channel (e.g. blue), the rows represent reasonably uniform steps in LCH luminance of the simulated color and a rich (high chroma) simulation at that luminance.

The last word on color palettes for color blidness. / Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Color ramps of 16–19 colors for each color channel for each color blidness type. Color ramps show RGB colors and their color blindness simulation grouped by channels (e.g. greys, blues, yellow). Within a channel, colors are sorted in increasing and roughly equal steps of LCH luminance of the simulated color. At a given luminance, the RGB color whose simulation has the highest chroma is used. (PDF)
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Propensity score weighting

Mon 17-03-2025

The needs of the many outweigh the needs of the few. —Mr. Spock (Star Trek II)

This month, we explore a related and powerful technique to address bias: propensity score weighting (PSW), which applies weights to each subject instead of matching (or discarding) them.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Propensity score weighting. (read)

Kurz, C.F., Krzywinski, M. & Altman, N. (2025) Points of significance: Propensity score weighting. Nat. Methods 22:1–3.

Happy 2025 π Day—
TTCAGT: a sequence of digits

Thu 13-03-2025

Celebrate π Day (March 14th) and sequence digits like its 1999. Let's call some peaks.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
2025 π DAY | TTCAGT: a sequence of digits. The digits of π are encoded into DNA sequence and visualized with Sanger sequencing. (details)

Crafting 10 Years of Statistics Explanations: Points of Significance

Sun 09-03-2025

I don’t have good luck in the match points. —Rafael Nadal, Spanish tennis player

Points of Significance is an ongoing series of short articles about statistics in Nature Methods that started in 2013. Its aim is to provide clear explanations of essential concepts in statistics for a nonspecialist audience. The articles favor heuristic explanations and make extensive use of simulated examples and graphical explanations, while maintaining mathematical rigor.

Topics range from basic, but often misunderstood, such as uncertainty and P-values, to relatively advanced, but often neglected, such as the error-in-variables problem and the curse of dimensionality. More recent articles have focused on timely topics such as modeling of epidemics, machine learning, and neural networks.

In this article, we discuss the evolution of topics and details behind some of the story arcs, our approach to crafting statistical explanations and narratives, and our use of figures and numerical simulations as props for building understanding.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Crafting 10 Years of Statistics Explanations: Points of Significance. (read)

Altman, N. & Krzywinski, M. (2025) Crafting 10 Years of Statistics Explanations: Points of Significance. Annual Review of Statistics and Its Application 12:69–87.

Propensity score matching

Mon 16-09-2024

I don’t have good luck in the match points. —Rafael Nadal, Spanish tennis player

In many experimental designs, we need to keep in mind the possibility of confounding variables, which may give rise to bias in the estimate of the treatment effect.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Nature Methods Points of Significance column: Propensity score matching. (read)

If the control and experimental groups aren't matched (or, roughly, similar enough), this bias can arise.

Sometimes this can be dealt with by randomizing, which on average can balance this effect out. When randomization is not possible, propensity score matching is an excellent strategy to match control and experimental groups.

Kurz, C.F., Krzywinski, M. & Altman, N. (2024) Points of significance: Propensity score matching. Nat. Methods 21:1770–1772.

Understanding p-values and significance

Tue 24-09-2024

P-values combined with estimates of effect size are used to assess the importance of experimental results. However, their interpretation can be invalidated by selection bias when testing multiple hypotheses, fitting multiple models or even informally selecting results that seem interesting after observing the data.

We offer an introduction to principled uses of p-values (targeted at the non-specialist) and identify questionable practices to be avoided.

Martin Krzywinski @MKrzywinski mkweb.bcgsc.ca
Understanding p-values and significance. (read)

Altman, N. & Krzywinski, M. (2024) Understanding p-values and significance. Laboratory Animals 58:443–446.

Martin Krzywinski | contact | Canada's Michael Smith Genome Sciences CentreBC Cancer Research CenterBC CancerPHSA
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