<p>Agglomerative hierarchical clustering (AHC) computation based on Ward's method (right panel).</p
<p>(A) Histogram of eigenvalues, (B) Principal Component Analysis (PCA) plot of factor loadings in t...
<p>PCA scores plot obtained from analysis of gene expression profiles. Proportion of the variance ex...
<p>(A) Dendogram. The colors of the branches represent the three largest clusters. (B) PCA biplot. A...
<p>PCA axes 1 and 2 account for 84.2% of the cumulative variance. The cluster analysis of the two ma...
<p>Biplots show the correlation vectors representing the projection (in 2 dimensions) of loading for...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
<p>Global, multivariate correlation analysis. On the Biplot each body location is represented by pol...
<p>The first and second axes of the PCA are shown. The length of the variable arrow corresponds to t...
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
Principal component 1 (PC1) in horizontal axis and PC2 in vertical axis explain 37% and 15% of varia...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
<p>Component correlation matrix of principal component analysis (PCA) used to determine relationship...
<p>The two leading principal components display the variance. The superimposed biplot shows the cont...
<p>A, B and C: Hyperplane between the first and second principal components (PC1 and PC2, respective...
<p>(A) Histogram of eigenvalues, (B) Principal Component Analysis (PCA) plot of factor loadings in t...
<p>PCA scores plot obtained from analysis of gene expression profiles. Proportion of the variance ex...
<p>(A) Dendogram. The colors of the branches represent the three largest clusters. (B) PCA biplot. A...
<p>PCA axes 1 and 2 account for 84.2% of the cumulative variance. The cluster analysis of the two ma...
<p>Biplots show the correlation vectors representing the projection (in 2 dimensions) of loading for...
Principal components analysis (PCA) is a multivariate ordination technique used to display patterns ...
<p>Global, multivariate correlation analysis. On the Biplot each body location is represented by pol...
<p>The first and second axes of the PCA are shown. The length of the variable arrow corresponds to t...
<p>In the row for each variable, numbers indicate the strength of correlation of that variable with ...
Principal component 1 (PC1) in horizontal axis and PC2 in vertical axis explain 37% and 15% of varia...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
Principal Component Analysis (PCA from now on) is a multivariate data analysis technique used for ma...
<p>Component correlation matrix of principal component analysis (PCA) used to determine relationship...
<p>The two leading principal components display the variance. The superimposed biplot shows the cont...
<p>A, B and C: Hyperplane between the first and second principal components (PC1 and PC2, respective...
<p>(A) Histogram of eigenvalues, (B) Principal Component Analysis (PCA) plot of factor loadings in t...
<p>PCA scores plot obtained from analysis of gene expression profiles. Proportion of the variance ex...
<p>(A) Dendogram. The colors of the branches represent the three largest clusters. (B) PCA biplot. A...