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The transcripts cluster analysis was achieved by using 'clustergram' of MATLAB (MathWorks, Natick, MA, USA).
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And all of the mtDNA CDSs of the 30 species used in clustering analysis were achieved from GenBank.
No functional analysis is achieved.
It should be noted, however, that the aim of cluster analysis was not to achieve the ideal clustering in light of the reference sets, but to show how the choice of similarity threshold influences the performance when the same clustering workflow and reference clustering sets are used for comparison.
The k-means cluster analysis was conducted with the regression factor scores and convergence was achieved in 12 iterations.
A hierarchical cluster analysis was performed, followed by a K-means cluster analysis.
First, a cluster analysis was performed, using model-based (Mclust) and variable clustering.
Hierarchical cluster analysis was also performed to emphasize natural clusters and patterns.
A cluster analysis was performed to detect consumers' profiles.
Cluster analysis was applied to classify the forest types.
Cluster analysis was undertaken using the BRB gene cluster analysis tool (complete linkage and centred correlation).
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