Sentence examples for between clusters were assessed from inspiring English sources
Stx2 production differences between clusters were assessed using the t-test function of R. In total, 10 serogroups and 12 unique serotypes were represented in the STEC panel.
More precisely, the optimum number of clusters to retain, which depends on homogeneity within cluster and/or heterogeneity between clusters, was assessed by RSQ, Semi-Partial R-Squared (SPRSQ), Root-Mean-Square Standard Deviation (RMSSTD) and the pseudo-F statistic (pF) [ 28, 29].
Two predominant profile clusters were identified and, for each array probe, differential expression between clusters was assessed using a moderated t-statistic (Bioconductor limma) with P-values corrected for the effects of multiple hypothesis testing over all probes using the false discovery rate (FDR) correction of Storey and Tibshirani (Storey and Tibshirani, 2003) (Bioconductor qvalue).
The degree of overlap between the clusters was assessed by calculating the number of holdings that were in both clusters and the percentage of the total number of holdings in each cluster.
The correlation between them and their ability to form homogeneous clusters is assessed.
Support for the detected clusters was assessed with the relative height values indicative of the genetic distance between clusters.
The performance of the model on that cluster is assessed as the correlation between the predicted expression profile over all conditions versus the observed expression.
Spatial clustering was assessed using the intracluster correlation coefficient, which may be interpreted as the expected correlation between any randomly selected pair of observations drawn from the same cluster.
