Exact(6)
Comparing unsupervised and supervised clustering results, it is likely that only a portion of the transcriptomal features distinguishing unsupervised clusters are associated with signaling, either directly or indirectly.
2. Investigate which feature groups form concrete unsupervised clusters, and associate these clusters with the existing medical knowledge.
A hierarchical clustering algorithm was used to identify unsupervised clusters based on the Euclidean distance for dissimilarities between the data samples.
A hierarchical clustering algorithm was used for finding (unsupervised) clusters based on the Euclidean distance for dissimilarities of gene expression profiles among the samples.
Of the 8 unsupervised clusters generated, the pattern of regulation in Clusters 7 and 8 led us to collapse them into Clusters 1 and 2 respectively.
PCA unsupervised clusters were CTRL samples (N = 6), HF FA (N = 6), and HF RCA NN = 6), which resulted in two subgroups (pre-ATH and ATH, N = 3 each) histologically corresponding to different ATS stage, as reported in Table 1.
Similar(54)
Results: Unsupervised clustering yielded several subgroups, or endotypes, of interest.
The technique is based on an unsupervised clustering of the three phase reactance step magnitudes.
Traditional pattern recognition generally involves two tasks: unsupervised clustering and supervised classification.
We set out to define distinct allergic phenotypes by unsupervised cluster analysis.
Unsupervised clustering revealed that the snoRNA expression subtype is highly concordant with other molecular/clinical subtypes.
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