Output | Copy Number | Correlation and Principal Variance Component Analysis

Running this process for the DrosophilaAgingExample sample setting generates the tabbed Results window shown below. Refer to the Correlation and Principal Variance Component Analysis process description for more information. Output from the process is organized into tabs. Each tab contains one or more plots, data panels, data filters, and so on, that facilitate your analysis.The Results window contains the following panes:This pane provides you with a space to view individual tabs within the Results window. Use the tabs to access and view the output plots and associated data sets.

• Variance Components Charts (Correlation and Principal Components): This tab shows both bar and line plots illustrating principal variance components.

• 3D PCA Plot (Correlation and Principal Components): This tab shows an interactive three-dimensional scatterplot of principal components.

• 2D PCA Plots (Correlation and Principal Components): This tab shows a two-dimensional scatterplot matrix of principal components.

• Scree Plot (Correlation and Principal Components) This tab shows a plot of illustrating the proportion of variability explained by principal components.

• Correlation Heat Map (Correlation and Principal Components): This tab shows a clustered heat map and dendrogram of the correlation matrix.

• Correlation Distributions (Correlation and Principal Components): This tab shows the distributions of the correlations and their associated p-values.

• SAS Output : This is a text-based output directly from SAS/STAT PROC PRINCOMP and PROC MIXED. The former provides detailed statistics on the principal components analysis. The latter contains one PROC MIXED run for each principal component to compute the variance component estimates for each. Refer to the documentation for SAS PROC PRINCOMP and PROC MIXED for more information.

• Correlation and Grouped Scatterplots: Click to launch the Correlation and Grouped Scatterplots process to generate scatterplot matrices of the raw data. The input data set used here is the preloaded in as input for the Correlation and Grouped Scatterplots process.

• Click to reveal the underlying data table associated with the current tab.

• Click to reopen the completed process dialog used to generate this output.

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• Click to close all graphics windows and underlying data sets associated with the output.