Multivariate analysis using principle coordinate analysis plot (PCO) revealed that expression patterns of the genes from these two categories exhibited distinct tissue-specific patterns.
However, multivariate analysis such as principle component analysis (PCA) and cluster analysis is widely used to explain the correlation amongst a large number of variables in terms of a small number of underlying factors without losing much information (Meglen 1992; Ogwoeleka 2015; Pazand 2016; Qian et al. 2016).
Rather than searching for a few diagnostic characters, a multivariate analysis, such as principle component analysis, may be more appropriate to dissect the morphological differences between P. putjatia and P. vlangalii.
Our data constitute a proof of principle that multivariate analysis of the transcriptome related to cell stress and inflammation of peripheral blood leukocytes has significant potential as a minimally invasive and inexpensive diagnostic tool for diagnosis and early detection of risk for AD.
The study was conducted using Design of Experiment (DoE) principles and multivariate analysis approach.
Multivariate analysis methods, such as Clustering analysis and Principle component analysis, were applied to determine the quality differences between samples.
Then, some crucial quantitative thermo-kinetic parameters including growth rate constant, heat-flow power and heat output, etc. were obtained from theses curves and were further investigated by some powerful chemometric techniques including similarity analysis, multivariate analysis of variance, hierarchical clustering analysis and principle component analysis.
The multivariate analysis will be performed along the same principles for variable selection and model building as outlined above.
In a principle component analysis (TD + T + RT + ET ∼ species), total travel distance explained less of the variation than did tortuosity in the first principle component, and was therefore dropped from multivariate analysis.
For the principle analysis of change in HbA1c a multivariate analysis using actual patient data was performed.
