Defining clusters from a hierarchical cluster tree: the Dynamic Tree Cut package for R

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WGCNA: an R package for weighted correlation network analysis (2008, methodology): “archical clustering dendrogram correspond to modules and can be identified using one of a number of available branch cutting methods, for example the constant-height cut or two Dynamic Branch Cut methods [ 29 ].”
Strategies for aggregating gene expression data: The collapseRows R function (2011, methodology): “of branch cutting parameters implemented in the dynamicTreeCut R library [20] were chosen to define 28 different module assignments.”
Insights into Ciliary Genes and Evolution from Multi-Level Phylogenetic Profiling (2017, methodology): “Gene clusters were defined as branches from the resulting dendrogram, using the dynamic tree-cutting algorithm (Langfelder et al. 2008).”
The role of atmospheric conditions in the seasonal dynamics of North American migration flyways (2014, methodology): “Second, we applied an adaptive branch pruning technique to identify the prominent flyway clusters in each of the 10,000 bootstrap dendrograms (Langfelder et al., 2008).”