Sentence examples for cluster package from inspiring English sources

All statistical analyses were performed by using the R software version 3.2.2 (R Development Core Team 2015) with the "vegan" package (Oksanen et al. 2012) and the "cluster" package (Maechler et al. 2015).

Hierarchical clustering was performed using complete linkage clustering with uncentered correlation as the similarity metric in the CLUSTER package [39].

Hierarchical clustering analysis was performed with R's cluster package, using the Pearson correlation distance.

This distance matrix was then used as the input for PAM clustering, available in the R cluster package.

Clustering of the samples into enterotypes was done using the cluster package 21 according to instructions available on http://enterotyping.embl.de.de

All clustering analyses employed divisive hierarchical clustering using the DIANA algorithm as implemented in the cluster package (v1.11.10) and with Pearson's correlation as a similarity metric.

Hierarchical clustering of differentially expressed genes was performed using the Cluster software package [ 92], using the function (1 - Pearson correlation coefficient) as the pairwise distance metric and the average agglomeration method.

For regression/parameters importance analyses and for cluster analyses, we used R's caret and cluster packages respectively.

Both algorithms were used as implemented in R (cran.r-project.org, in the stat and cluster packages).

All analyses were done with R by using the limma, survival, and cluster packages.

Correlation plots and hierarchal trees were generated using cluster packages available in R. Gene ontology over-representation was analysed using GOTree Machine, normalising to the U133A 2.0 gene set, with significance set at P < 0.01 [ 81, 82].