title: GeoPCA: a new tool for multivariate analysis of dihedral angles based on principal component geodesics.
abstract: The GeoPCA package is the first tool developed for multivariate analysis of dihedral angles based on principal component geodesics. Principal component geodesic analysis provides a natural generalization of principal component analysis for data distributed in non-Euclidean space, as in the case of angular data. GeoPCA presents projection of angular data on a sphere composed of the first two principal component geodesics, allowing clustering based on dihedral angles as opposed to Cartesian coordinates. It also provides a measure of the similarity between input structures based on only dihedral angles, in analogy to the root-mean-square deviation of atoms based on Cartesian coordinates. The principal component geodesic approach is shown herein to reproduce clusters of nucleotides observed in an η-θ plot. GeoPCA can be accessed via http://pca.limlab.ibms.sinica.edu.tw.
authors.affiliation: Institute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan. karsar@ibms.sinica.edu.tw
authors.forename: Karen
authors.initials: K
authors.lastname: Sargsyan
authors.forename: Jon
authors.initials: J
authors.lastname: Wright
authors.forename: Carmay
authors.initials: C
authors.lastname: Lim
mesh_terms: D016000:Cluster Analysis; D015999:Multivariate Analysis; D009690:Nucleic Acid Conformation; D025341:Principal Component Analysis; D012265:Ribonucleotides / Q000737:chemistry; D012984:Software
chemical_list: D012265:Ribonucleotides