The proteins considered in the unsupervised
hierarchical clustering analysis were quantified in individual samples and found to be significantly different in abundance by analysis of variance (ANOVA p ≤ 0.01, Table S3); while PCA analysis considered all proteins quantified in each individual sample.
A further semi-objective classification using
hierarchical cluster analysis is in line with these classifications, supporting the metadata approach.
The cluster dendogram was generated using
a hierarchical cluster analysis in R (http://stat.ethz.ch/R-manual/R-patched/library/stats/html/hclust.html).
Microarray hybridization patterns were interpreted using
hierarchical cluster analysis as previously described [65], [66].
Proteins (n = 59) that were quantified and determined to be significantly different in abundance by ANOVA (p ≤ 0.01) when comparing CFS from nPTLS subject samples and allow for separation of these two syndromes when performing unsupervised
hierarchical cluster analysis.
Hierarchical cluster analysis was applied, and four time perspective patterns were distinguished with some significant differences in students academic procrastination and interest in decreasing it.
In order to reveal more specific associations between eating behavior and the parent — child relationship, eating behavior subgroups derived from
hierarchical cluster analysis were used (Schacht et al., 2006).
Not exact matches
(A) Heat map illustrating
hierarchical clustering of differentially expressed genes identified in a pair-wise
analysis of all four fractions.
Hierarchical clustering with heat map
analysis revealed that the 39 tumors as well as the re-extracted VP62 (2012) sample were negative for XMRV (Fig. 2, «2012»).
Correlation of differentially expressed transcripts was detected by
hierarchical clustering of expression values with the
Cluster version 2.11 software [52] applying mean centering and normalization of genes and arrays before the computational
clustering analysis.
Transcriptomics
analysis of inguinal WAT showed a marked effect of cold on overall gene expression, as revealed by principle component
analysis and
hierarchical clustering.
Specific statistical areas of expertise include factor and
cluster analysis, basic bivariate
analyses, repeated measures
analyses, linear and
hierarchical / mixed models, structural equation modeling, and nonparametric
analyses including logistic regression techniques.
Preliminarily assuming that there are three factors, we performed an oblique rotation (oblimin) for explanatory factor
analysis and
cluster analyses (
hierarchical and non-
hierarchical methods) with the N - GED48 scale.
Further, we excluded similar question items based on
hierarchical and non-
hierarchical cluster analyses.