The following tweet was very popular on when shared on our @Plantae_org Twitter account April 10th, 2019


"To democratize state-of-the-art data visualization data with a selection of statistical summaries, Postma and Goedhart have created an open-source, and user friendly web app was using R/shiny and  the ggplot2 package. Give it a try! 



I highly recommend checking out Postma and Goedharts's paper and playing around with their software and visualization options. It is extremely simple to use, doesn't require any downloads, and is a fun way to visualize data.


Here is a list of papers (shared by @natureplants on Twitter) explaining why researchers should look beyond the bar graph:

https://www.nature.com/articles/s41551-017-0079

https://www.nature.com/articles/nmeth.2837

https://journals.plos.org/plosbiology/article?id=10.1371/journal.pbio.1002128

http://www.jbc.org/content/292/50/20592.full

https://ecrlife.org/2018/07/10/beyond-bar-graphs-free-tools-and-resources-for-creating-more-transparent-figures-for-small-datasets/


One note of caution: 

When this was shared on Twitter, Daniel Kleibenstein (@SpicyBotrytis) brought up a good point saying "Just remember that this is not a universally applicable solution. There are experimental designs and experimental scales that overwhelm the showing of individual data points." 


If you know of other cool resources like this one feel free to share them in the comment section below!