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In the present study, changes in hexose concentration induced by stress did not contribute to Cluster distinction.
Cluster distinction was measured using cluster average posterior probabilities (AvePPs), where a value of above 0.7 represents clear separation.
Accordingly, if statistical fit indices suggested complex models with diminutive improvement, and models with few clusters gave similar levels of cluster distinction, we would choose the model with the fewer number of clusters.
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For FFPE samples, there was no clear clustering distinction between naevi, primaries and metastases, perhaps reflecting the molecular heterogeneity of melanoma.
Among the DLBCLs, we observed several distinct clusters, without distinction between de novo and transformed DLBCLs.
The clustering quality is measured in terms of the density of the clusters, as well as the distinction between clusters and the closeness of the clusters to some reference clusters.
The times to repeat the clustering depends on the distinction in clustering data.
In this cluster, a noteworthy distinction among tolerant and sensitive genotypes is that, in both rice and barley sensitive genotypes, a more significant proportion of the genes related to osmosensing and salt stress are down-regulated.
The method attempts to optimise between-cluster variation whilst minimising variation within clusters, thus producing a clearer distinction of clusters [ 80].
In the hierarchical clustering, the greatest distinction in response profiles was between this subset of enabler resistant cells and the other two groups.
In this analysis, we excluded nuclei that were in the immediate vicinity of neuromuscular synapses, because they often show clustering, impeding the distinction of individual features; moreover, synaptic nuclei are functionally specialized to synthesize constituent proteins of the postsynaptic apparatus, whereas this does not apply for more distant myonuclei (21– 21).
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