Page History
...
the principal components analysis (PCA) scatter plot allows us to visualize similarities and differences between the samples in a data set.
- Click the Gene Counts Normalized counts data node
- Click Exploratory analysis in the task menu
- Click PCA
- Click Finish to run PCA with the default options
...
| Numbered figure captions | ||||
|---|---|---|---|---|
| ||||
|
- Double click the PCA task node to open the PCA scatter plot (Figure 2)
| Numbered figure captions | ||||
|---|---|---|---|---|
| ||||
|
The scatter plot shows each sample as a point in a three dimensional plot. The x, y, and z axes are the first three principal components. The percentage of total variance explained by each is listed next to the axis label. The size of each axis is determined by the variance along that axis. The plot is fully interactive; it can be rotated and points selected.
...
Overview
Content Tools