A biplot overlays a score plot and a loadings plot in a single graph. In the biplot view, points are the projected observations (samples); vectors (arrows) are the projected variables. If the data are wellapproximated by the first three components, a biplot enables you to visualize highdimensional data by using a 3D space. You can visualize both the patterns (sample distributions) and the features that driving such patterns.
 Points that are close to each other in the biplot represent observations with similar values.
 The cosine of the angle between pairs of vectors indicates correlation between the corresponding variables. Highly correlated variables point in similar directions; uncorrelated variables are nearly perpendicular to each other.
 The cosine of the angle between a vector and a principal component axis indicates the contribution of the corresponding variable to the principal component: the more parallel to an axis is a vector, the more it contributes only to that PC.
To perform biplot visualization:

Select “Biplot (merged view)” under View options in the top menu bar.

Select omics type, features to be displayed and color of arrows using the dialog

Biplot visualization: each arrow represent a feature, top 5 features based on differential expression analysis from each dataset are displayed here.