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Cluster 1 had the greatest PD and CAL; there were significant differences between the clusters for PD and CAL.
Figure 4 shows a heat map representation of the similarity between the clusters for all the datasets.
A very clear separation between 16 tested HNC patients and 26 healthy subjects can be observed, with no overlap between the clusters for the small study population.
The seven cluster solution allowed enough detailed separation between the clusters for adequate distinctiveness and discrimination between them, while also being parsimonious without being overly complex.
The non-response on BMI was different between the clusters for boys, with the highest rates in the unhealthy behavior cluster (43.1%) and the mixed cluster (42.7%) and lowest in the healthy behavior cluster (36.2%).
In addition to normal clustering requirement of high inter-distance and low intradistance between the clusters, for efficient indexing purposes, we require that the size of clusters are balanced, that is clusters should have similar number of data points.
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Instead, information is shared via a common hyperparameter, α0, between the clustering for each dataset.
An analysis of the socio-demographic characteristics does not point out particular differences between the clusters except for those related to age.
Baseline characteristics were similar between the clusters except for a higher frequency of water distribution in the intervention clusters (table 1).
A Kruskal-Wallis (KW) test was performed to identify miRNA differentially expressed between the clusters identified for both tumor and non-malignant tissues.
The results have demonstrated that there is high overlap between the gene clusters for the incomplete data set and those for the complete data set, which illustrates the robustness of the WDCM on clustering the incomplete data set at low percentage of missing values.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com