Monday, September 9, 2013

A case against color-merges to show colocalization

- Gautham

Seeing as a recent post has revealed to the public my distaste for certain common scientific data display and presentation techniques (laser pointers, 3d plots and color-merges), it seemed a good time to explain why I'm not into these things. The color-merge comes first. I'll explain why I think it is a too-clever trick that is best replaced with showing each image separately.

It is often intended to show that signals in two different imaging channels, usually two fluorescent dyes or proteins, arise from the same underlying objects, or "colocalize." Scientists commonly find it necessary to take the two images, invariably collected in black and white, false-color them and superimpose them using some form of color-combining (usually an additive color model). Then you show a figure where you say that A and B where false colored red and green and look, in the combination all the features are purple. Or is it orange? Actually, what is the sum of red and green? Or are we subtracting red and blue from white? Isn't red plus green black?

I think this is the root of the problem with color merging for co-localization. We have no innate skill at combining colors. I have to look up a color wheel, or remember my elementary school painting class, to determine what the combination of two colors is supposed to be. Take a look at the wikipedia page for and ask yourself if you get any idea for the full color print by looking at the CMYK decomposition. Aside from painting, when do we ever combine colors? When did our ancestors' lives or reproductive potential depend on their ability to sum red and green?

On the other hand, we are good at recognizing visualizing patterns. We do so innately and struggle to program a computer to match our capabilities. We can recognize a person's face in a caricature or in a minimalist hand drawing or despite considerable digital distortion and no matter what else is in the background. When two images are images of the same thing, we can tell. Plus, there is no need for chromatic-shift correction to make the point.

A corollary of these arguments is that color-merging is actually not too bad at showing lack of colocalization or simply to overlay two totally different types of images. For example, if you show diffuse immunofluorescence in one color and punctate RNA-FISH in another color and add them up. This does not demand that we add colors, and is a useful help for us to judge the spatial relationships between these two stains. It is analogous to having a foreground and a background in a picture. You can also color-merge two different punctate signals that do not co-localize and not do much harm (though it may be a wasted effort).

In short, if it can be avoided, don't require us to add colors.

Here are some other things that are sacrificed when color merging:

  • For a co-localization merge, it is difficult to deal with the background and the signal in each image in a consistent way and still deliver your message. Unless the two images are linear transformations of each other, it will be impossible for the whole co-localized image to be the same color, despite perfect co-localization of the signal.
  • Co-localization merge requires that not only the positions of the features be the same but that the ratio of intensities of the features in the two channels be always the same. It is quite difficult to know if a little bit of red has been added to green. 
  • You give up the freedom to independently contrast and colormap your separate images, which is very important when dealing with data that contains features at widely different intensities. You can then use color very effectively to encode intensity within each channel's image, and let our ample pattern recognition capabilities judge the overlap between channels. 

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