Visualisation Principal component visualisation PCA visualization PCA plotting Principal modes visualization The use of Principal Component Analysis (PCA), a multivariate statistical analysis to obtain collective variables on the atomic positional fluctuations, helps to separate the configurational space in two subspaces: an essential subspace containing relevant motions, and another one containing irrelevant local fluctuations. Microarray principal component rendering Examples for visualization are the distribution of variance over the components, loading and score plots. Principal component plotting Visualize the results of a principal component analysis (orthogonal data transformation). For example, visualization of the principal components (essential subspace) coming from a Principal Component Analysis (PCA) on the trajectory atomistic coordinates of a molecular structure. ED visualization Essential Dynamics visualization beta12orEarlier Microarray principal component plotting