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Encouraging the use of bar plots over Venn Diagrams
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README.md

Binder Click the button to launch a Binder R session and tinker with all the bar plots or explore the code in the cloud. Navigate to the examples directory where there is a subdirectory for each of the four examples, all identified by the first or last author.

Venn diagrams are a type of figure that I see a lot in the literature. While Venn diagrams are a great way to conceptualize the goal of looking for shared or unique transcriptional responses to experimental manipulations, I don’t think they are the best way to vizualize empirical data.

I searched for “Venn” in Garrett Grolemund & Hadley Wickham’s R for Data Science book and in Claus Wilke’s Fundamentals of Data Visualization book, for guidance alternatives to the Venn diagram. Neither book discusses Venn diagrams, but they both provide valuable insight into creating bar plots. Interestingly, the R for Data Science book does use Venn diagrams to illustrate the differences between inner_join and full_join, so that provides some evidence that Venn diagrams are useful for conceptualizing ideas about data.)

The UpSet plot has gained some popularity since 2016. I’ve made a handful of UpSet plots with upsetR. While it is possible to modify the aesthetics of an UpSet plot, it is very challenging to manipulate the size, shape, colors, and font to the degree that is needed to combine many plots into one multi-panel figure for a manuscript.

In this repository, I turn 12 Venn diagrams from published research articles to four bar plots made with tidyverse and cowplot. I think these bar plots can be made more simplicity, flexibility, reliability, and reproducibility than a Venn diagram.

Let me know what you think!

Example 1 is inspired by “Cognitive specialization for learning faces is associated with shifts in the brain transcriptome of a social wasp”" by Berens et al. 2017.

Example 2 is from “Transcriptomics of an extended phenotype: parasite manipulation of wasp social behaviour shifts expression of caste-related genes”" by Geffre et al.

Example 3 is from “Sex-biased transcriptomic response of the reproductive axis to stress”" by Calisi et al 2017.

Example 4 is from “Early life stress alters transcriptomic patterning across reward circuitry in male and female mice”" by Peña et al. 2017.

So, that’s my comparison of four Venn diagrams and four possible bar plot alternatives. What do you think? Do you see the advantages? What other alternatives do you suggest? Comments welcome!

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