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This one-sided test for clustering was implemented in an Excel spreadsheet program (Microsoft Corp., Redmond, WA).
The clustering was implemented using R version 3.4.0 (Supplementary Files 6 and 7).
Clustering was implemented by storing more than one object in a single database tuple.
Plots were generated using matplotlib [38] and clustering was implemented in the Python programming language using the SciPy package [39].
Hierarchical clustering was implemented using common similarity measures and linkage methods (See supplementary equations) [ 18, 39].
Hierarchical clustering was implemented using the R hclust program (Step 5 in Figure 1).
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Fourth, mean-shift clustering is implemented to merge or split labeled regions.
Several clustering methods (hierarchical, SOM, K-means and Terrain clustering) were implemented using the program Genesis.
Hierarchical clustering is implemented for grouping the pathways into clusters by using the dynamicTreeCut package in R [ 45] (see Figure 5(c)).
Hierarchical clustering is implemented using a new parallelized O(N) algorithm (Müllner, 2013; Murtagh 2011: http://labs.genetics.ucla.edu/horvath/CoexpressionNetwork/Rpackages/flashClust) instead of the O(N) hclust algorithm used in Clusco.
Our phase synchronization analysis of β-cell clusters was implemented in Matlab.
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