View on GitHub


Interactive exploration of the natural variation in Arabidopsis Root System Architecture under salt stress


This Application was build as a supplement to the paper “Genetic components of root architecture remodeling in response to salt” by Magdalena M. Julkowska Iko Koevoets, Selena Mol, Huub Hoefsloot, Richard Feron, Mark A. Tester, Joost J.B. Keurentjes, Arthur Korte, Michel A. Haring, Gert-Jan de Boer, Christa Testerink. Published in Plant cell, DOI:

The App was build to allow interactive exploration of the natural variation in Root System Architecture of Arabidopsis thaliana.

The App can be either accessed here or here or run locally from your device by typing the following command in your R window:


shiny::runGitHub("mmjulkowska/Salt_NV_RootApp", "mmjulkowska")

The code underlying the App is freely available at the github for use and reproduction or tweaking to your own results.

What can you do with the App:

1. Examine how salinity alters the phenotypes of individual accessions

To compare the RSA phenotypes of individual accessions between different conditions studied in our study (0, 75 or 125 mM NaCl), the user can select the accession from the menu either by clicking on one, or starting to type its coloquial name.

alt text

The user can change the phenotype in the side panel. The histogram below the graph is showing the natural variation observed in the entire HapMap population examined in our study.

2. Compare the RSA phenotypes for significant differences between 8 accessions

To compare the phenotypes of (up to) 8 different accessions, please select the accessions in the side panel. If you wish to select less than 8 accessions, just repeat the name of some accessions in the individual boxes.


The letters above the graph represent the significantly different groups as per Tuckey pair-wise test with p-value of 0.05.

3. Examine the correlation between individual RSA traits at different conditions

To examine the correlations between the individual RSA traits in control or salt stress conditions, you can pick a phenotype on the side panel and examine the distribution of the accessions in the scatter plot. You can identify individual accessions by putting your coursor over the dot, revealing the accession name and its coordinates.


The correlations were performed using Pearson correlation method.

4. Cluster the accessions based on the three traits of your interest

The individual accessions will cluster into different groups depending on the traits that are used. We have our favourite traits, but we do not exclude the possibility that other scientists might have a different opinion on importance of the RSA traits - either driven by their interest in RSA development exclusively under control conditions, or RSA phenotypes related to root zonation.

Therefore, we developed the feature allowing users to perform their own clustering analysis on the unlimited number of traits.


In Step 1 the user can chose up to three phenotypes to perform the clustering.

The relationship between the accessions is established depending on the chosen phenotype. For calculating the relationship between the accessions we used Ward’s Hierarchical Clustering Method (ward.D2).


In Step 2 the user has to chose at what distance would the dendrogram tree be cut. The dendrogram representing the relationship between the accessions can be found in the second sub-tab of “Cluster Analysis”.


The cluster validation can be performed in Step 3, where the individual accessions are grouped depending on their cluster belonging. The individual phenotypes can be selected in the side panel.


The file containing the data on which accessions belong to which cluster can be downloaded from Step 4 tab.

Happy data exploration!