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This approach performs clustering and subsequent Rand index scoring at all possible dendrogram height cutoffs using supervised cut height training on the ground truth data.
Modules were merged if their similarity was greater than 0.3 according to dendrogram height.
The results are presented as a heat-map of gene expression similarity, using a cluster dendrogram height of 1.3.
Using the H-clust function (an in-house R script), super clusters were defined at a dendrogram height equal to 3. The clusters were represented on a heat map drawn using an in-house R script [ 42].
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Merge scores correspond to dendrogram heights.
By cutting the clustering dendrogram at height 60, we obtained four well defined clusters.
A total of 28 clusters were produced by cutting the dendrogram at height 0.75.
Hierarchical clustering based on the HR MAS MR spin echo spectra revealed three clusters that were convincingly separated when selecting a threshold of the dendrogram at height 0.39.
Unsupervised hierarchical clustering with complete linkage was performed using Spearman's correlation as similarity measure, identifying three luminal A groups by cutting the dendrogram at height 0.39, which was decided as a threshold that gave convincing separation between groups.
In order to construct a full dendrogram (with heights) for the studied proteins, we have used the harsher criterion throughout our analysis.
Additional analysis revealed that the orders between iMR1_799, iMR4_812, and iW3181_789 can switch with just a few changes in the genes considered due to the small differences in the dendrogram branch heights.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com