In subgroup analysis grouped by ethnicity, no significant association was detected.
Cluster analysis grouped 25 genotypes into two main groups and four clusters.
The clustering analysis grouped all the images into 25 clusters with the highest internal and the lowest external similarities.
Our analysis grouped 1 sampling site into four seasons for understanding temporal variation in water quality characteristics.
The 16S rRNA sequence analysis grouped the isolates into the following genera: Pseudomonas, Bacillus, Psychrobacter, Vibrio, Citrobacter, Enterobacter, and Bosea.
It is visible that the cluster analysis grouped the whole samples into three distinct groups of cluster.
Cluster analysis grouped the physico-chemical parameters into three distinct groups (physical/minor ions, major ions and trace elements).
Hierarchical cluster analysis grouped 35 surfacewater sources into three statistically significant clusters based on the similarity of water quality characteristics.
All the 75 genotypes used in our study were from the indica subgroup but the structure analysis grouped them into three subgroups (K = 3) with admixtures.
This first analysis grouped the researchers in terms of received indications, which can be seen as in-degree measure of graph centrality.
The cluster analysis grouped runoff water samples into two clusters based on the similarity of runoff water quality characteristics of the total variance.
