Miall

Morgan

Ross

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Using colour in figures: let’s agree to differ

Levine, T.

UCL Discovery

# 2009 The AuthorJournal compilation # 2009 Blackwell Munksgaarddoi: 10.1111/j.1600-0854.2008.00863.xTraffic 2009; 10: 344–347Blackwell MunksgaardTraffic InterchangeUsing colour in figures: let’s agree to differTim LevineDepartmentofCellBiology,UCLInstituteofOphthalmology,Bath Street, London EC1V 9EL, UK, tim.levine@ucl.ac.ukKey words: accessibility, colour blind, data presentation,deuteranomaly, deuteranopia, dichromat, trichromatReceived 21 October 2008, revised and accepted forpublication 25 October 2008, uncorrected manuscriptpublished online 4 December 2008A picture can paint a thousand words, and cell biologistsparticularly rely on pictorial representations. It is nowstandard to use colour in pictures from graphs to micro-graphs. Apart from being appealing, colour can be justi-fied on the basis that it adds information. However,a minority of people do not have the full range of colourvision (so-called ‘colour blind’), and this minority are toooften excluded by ill-conceived use of colour. This articlenot only suggests ways to maximize the accessibility ofcolour images to the minority but also shows that manyimages in the field of membrane traffic cannot be viewedoptimally by all, no matter what way they are treated.Colour vision is ancient in evolutionary terms, originallyconsisting of blue and yellow cones only (Figure 1A). Inrecent primate evolution, a duplication of the yellow opsin(on the X chromosome) has led to green–red discrimin-ation. In terms of human cone numbers, this axis faroutweighs the older one, with blue cones being relativelysparse. Thus, an individual with the full range of colourvision can accurately discriminate an entire spectrum ofcolour hues along the green–red axis better than along anyother colour axis (for example green–blue). Note thathumans differ considerably from digital cameras and videoscreens, where all colours are treated equally (Figure 1B).The paired green–red opsin genes often undergo partial orcomplete gene conversion leading to functional loss ofgreen–red discrimination, again partial or complete. Theincidence of the gene-converted haplotype is quite high inall racial groups; for example, 8% in Caucasians, where theincidence of the phenotype is 8% in males and 0.5% infemales. The minority that lacks the full range of colourvision is commonly referred to as colour blind but almost allsee some colour. Another argument against the common‘‘colour blind’’ term is that it is politically undesirableto consider the genetic majority as better, particularlybecause ‘defective’ genes are the source of social dis-crimination in some countries. To avoid this, colour visionis here divided into the majority and minority types.There is good evidence that loss of the green–red axis isa balanced polymorphism, as under some circumstancesthe inability to distinguish green and red is beneficial (1).However, in cell biology presentations of the current day,it can cause considerable problems. So, how can themajority apply colour to their data without excluding theminority? Unfortunately, there is no quick fix, but witha moderate amount of thought, their results can bepresented so that everyone can appreciate them. I haveidentifiedthreecategoriesofimagesthatneed tobetreateddifferently.Category 1 applies to all diagrams, including graphs(Figure 2). Simple adaptations help rapid processing ofthe information, with the minority colour vision typescatered for by choosing the colour palette carefully. Theserules should beapplied in allwalks oflife as there isnothingspecific to membrane traffic here. For example, the WorldWide Web Consortium published in 1999 a set of WebContent Accessibility Guidelines (WCAG version 1.0) thathave become the internationally accepted standard (www.w3.org/TR/WCAG10/). This includes simple advice on theuse of colour.Multiple micrographs of the same structures are the verystuff of membrane cell biology and particularly common inthis journal. The common practice is to merge green andred images, which can produce a third channel (yellow)that (in very simplistic terms – see below) indicates thedegree of overlap. But, as described above, people withthe minority form of colour vision are specifically unable toaccess green–red merges. So, a solution should be soughtfor presenting these images to >99.9% (compared with95%) of an audience. That something should be done isoften agreed upon, for example in a recent spate of corres-pondence in Nature (2–4). However, no one has yet agreedon one simple algorithm. In my opinion, the solution lies inapplying some intelligence – each presenter needs tounderstand a little bit about the problem and treat imagesaccording to their contents. Specifically, we need to makea judgement about the overlap being presented: is theoverlap qualitative (important in a gross manner) or is itquantitative (important in fine detail)?Re-use of this article is permitted in accordance with theCreative Commons Deed, Attribution 2.5, which does notpermit commercial exploitation.344 www.traffic.dkFigure 1: The human visual system is trichromatic but doesnot treat colours equally. Hue and saturation are represented ina single two-dimensional colour wheel. Hue varies around thewheel, and saturation increases with distance from the centre.This colour wheel shows colours at maximum brightness (i.e. withno added black). Primary colours are indicated. A) The humancentral nervous system is trichromatic by applying two colouraxes: I. Blue/yellow (through green) – which is ancient; II. Red/green (through yellow) – which is recent. We never experienceyellowish blue, or greenish red; instead, we are equipped toperceive a spectrum of many hues along each axis. B) Digitalscreens are trichromatic treating the three primary colours equallyin the RGB system. Red/green merges created in silico by cellbiologists are similar to the naturally occurring red/green axis, withoverlap perceived in a continuous spectrum of hues red4yellow4green. By comparison, axis III: magenta/green, whichcanbeeasily createdinsilico andwhichhas beenproposedto helpthe minority who lack a green or red opsin, uses only two hues:magenta and green and passes through the white (0% saturated)centre of the colour wheel. For the minority, the small amount ofinformation in axis III is a distinct improvement over their inabilitytouse axis IIatall. However, thehumanbrainispoorlyequippedtoassess degree of saturation, so the majority find axis III far lessinformative than axis II. The result of this is that no singletreatment suits presentation of complex colour images to allpeople. Instead, different images must be treated according tothe information they carry (Figures 2–4).% activity remaining0501000 10 20 30 40abcdefghAB0501000 10 20 30 40Beads added (AU)% activity remainingabcdefghBeads added (AU)CMYK (%)RGB(0-255 scale)RGB(% approx)Black 0,0,0,100 0,0,0 0,0,0Reddish purple   10,70,0,0 204,121,167 80,50,70Yellow 10,5,90,0 240,228,66 95,90,25Sky blue 80,0,0,0 86,180,233 35,70,90Vermillion 0,80,100,0 213,94,0 80,40,0Orange 0,50,100,0 230,159,0 90,60,0Bluish green 97,0,75, 00 ,158,1 15 0,60,45100,50,0,0 0,114,178 0,45,70 BlueCFigure 2: Some colours are more equal than others. A and B)The two graphs show a single experiment relating to a pull downof an activity on beads. A) The graph uses the default settingsprovided by MICROSOFT EXCEL. B) The graph has been adjusted tomake the data sets clearly identifiable. In general, diagramsshouldbe designed so that if viewed in black and white they still work.Colour can add ornamentation but should not be essential. Themost important changes are to enlarge symbols and thicken lines.When choosing colour, avoid pure red, green or blue and varybrightness as well as hue (Figure 1). Also, in legends, do not referto data sets by their colour, which may not be recognizable by theminority. C) A palette of colours suggested by Masataka Okabeand Kei Ito (Tokyo), which are distinguishable by most of theminority with poor or no green–red discrimination.Traffic 2009; 10: 344–347 345Using colour in figures: lets agree to differUntil now, the green–red axis (which is impenetrable to theminority) has been used to present almost all mergedimages. I suggest that in future, this should be used onlywhere strictly needed (see category 3 below). I suggestthat category 2 images be considered all those simple two-colour images that donot need the full range ofinformationoffered by the green–red axis. The distinguishing feature ofthese images is that the two channels contain informationof quite different types, for example two unrelated sub-cellular structures (Figure 3). Here, the areas of overlap areeither not obvious at all, or relatively large and veryobvious. The overlap is quantal (yes/no), and there is noneed for a viewer to assess the precise degree of mixingbetween channels, so they do not require the subtletiesafforded to the majority by the green–red axis. To presentcategory 2 images, the most widely accessible merge is tohave one channel green, the other magenta, with themerge colour being white (Figure 1B). This is very easilyachieved when starting from green–red RGB images bypasting the information in the red channel into the (empty)blue channel (Figure 3B). If a third image of the same cellsis also to be merged, as long as it shows similarly simpleinformation, such as a nuclear counterstain, the third (blue)channel can be included in the merge. Here, instead ofcreating green–magenta merges, more complex algo-rithms may be used, for example the one linked to athttp://www.vischeck.com/daltonize (Bob Dougherty, Stan-ford and Alex Wade, Smith-Kettlewell), which increasesseparation between green and red.What about images of highly overlapping data? Membranecell biologists often produce images of two or threepartiallycolocalizingpunctateintracellular markers(Figure 4).Here, the extent of overlap is absolutely key. In thesecases, green–red merges (Figure 4A), because they usethe pathway that is by far the best-developed, are notice-ably more informative than green–magenta images (Fig-ure 4B). It would be a mistake for the minority to insist thatthe majority forego the highly useful and unique resourceof green–red merges (2,4) because of their whole range ofintermediate hues (Figure 1A). By comparison, green–magenta merges only have two hues, and the spectrumis created by varying saturation, where the visual systemcannot easily distinguish intermediates (Figure 1B). Inthese instances, therefore, green–red merges should bepreserved despite the fact that they are not readable by theminority.Figure 3: Simple two-colour micrographs where overlap isnot crucial. Images of Arabidopsis hypocotyl cells labelled for thechloroplasts and microtubules. A) Falsely coloured green/red,microtubules in green and chloroplasts in red. The two subcellularorganelles sets landmarks for each other, and assessment ofdegree of overlap is not critical. Note that although the originalfluorophores were similar to these colours (e.g. microtubuleswere decorated with GFP), the image could easily be shown withthe colours reversed.B) A green/magenta image of thesame data.With theimagein RGB mode,all theinformationin thered channelwas copied into the clipboard and pasted into the blue channel.The result is more informative for the minority, and does notreduce information for the majority,becausethe spectrumof hueson the green–red axis is not important. Image kindly provided byJuliet Coates (Birmingham, UK).Figure 4: Complex two-colour micrographs where overlap iscrucial. Images of two markers with punctate distributions insidemammalian cells detected by immunofluorescence (kindly pro-vided by Adam Grieve, UCL, London). A) Green/red merge – thestandardmethod.B) The same dataas a green/magenta merge.C)The two separate images in black and white. Arrows marking themostprominentdouble-positive punctawerecreatedon onepaneland placed identically on other panels using the ‘Align’ function(available in software such as ADOBE ILLUSTRATOR or MICROSOFTPOWERPOINT). While an image such as (A) contains maximalinformation for the majority, it is useless for the minority. Otherimages should be made available to allow the minority to assessoverlap. B) The image does not use the trichromatic colour systemof the majority to maximum advantage and is only partially usefulto the minority for the same reasons. C) The image provides extralight, but the appreciation of overlap must be indirect. While this isnot ideal, it does allow for careful (although non-intuitive) analysis,which is my preferred option for the minority.346 Traffic 2009; 10: 344–347LevineFor category 3, the minority must still be catered for, byshowing the separate channels in individual greyscaleimages.Here,itisvitalthatthepreciserelationshipbetweenthe two channels is indicated, usually by arrows placedidentically on the two separate images (Figure 4C). Assomeone with minority colour vision, I can vouch for thisapproach. In a journal where printed space is lacking, thesepanels can be published as supplementary information on-line. In data presentations, be they to large conferences orto small lab meetings, the extra panels can be shown bytoggling between the two images placed (and labelled witharrows) identically on successive slides. An important pointabout single channel images is that they should always be inblack and white – never falsely coloured (which is often donesolely to remind the reader of the colour used on a sub-sequent merge panel). This is because colours provide farless optical information than white. This applies especiallywhen images are printed, when as much as 50% of thebrightest pixels will be saturated with maximum ink levels.Here, I have suggested a way to categorize and treatcolour images so that close to 100% of people can accessthem, as opposed to 95%. Maybe, given the high pro-portion of category 3 images generated by the field ofmembrane traffic, our discipline should lead the way indefining standards for the use of colour in science andsociety at large. We should work to develop a consensusposition that can be adopted by international journals andnational/international scientific societies. At heart, ashinted at by the majority/minority terminology I have used,the question is political (very much with a small ‘p’). Whenyou next present your work, are you prepared for 1 in 20 ofyour audience to not get the picture?AcknowledgmentsI would like to acknowledge the Wellcome Trust for supporting work in mylaboratory and supporting the online open access publication of this article.Much of my ideas were learnt from the work of Kei Ito, University of Tokyo.He has campaigned successfully for changes in use of colour throughoutJapanese society and with Masataka Okabe runs the excellent websitehttp://jfly.iam.u-tokyo.ac.jp/color/. This provides many more details, includ-ing how they have helped designers working in many areas of Japanesesociety, from textbooks to Tokyo subway stations. In addition,I thank AdamGrieve (UCL, London), Andrew Stockman (UCL), Catherine Rabouille(Utrecht), David Stephens (Bristol) and Juliet Coates (Birmingham, UK) foruseful discussions and images.References1. MorganMJ, Adam A,Mollon JD. Dichromats detect colour-camouflagedobjects that are not detected by trichromats. Proc Biol Sci 1992;248:291–295.2. Miall C. Readers see red over low-impact graphics. Nature 2007;445:147.3. Runions J. Magenta and yellow in images is not a bright idea. Nature2007;445:364.4. Ross JA. Colour-blindness: how to alienate a grant reviewer. Nature2007;445:593.Traffic 2009; 10: 344–347 347Using colour in figures: lets agree to differ

Colour-blindness: how to alienate a grant reviewer. Nature 2007;445:593. Traffic 2009; 10: 344–347 347 Using colour in figures: lets agree to differ

Dichromats detect colour-camouflaged objects that are not detected by trichromats.

Magenta and yellow in images is not a bright idea.

Readers see red over low-impact graphics.

Using colour in figures: let's agree to differ

Using colour in figures: let’s agree to differ

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