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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 ?-? plot. GeoPCA can be accessed via http://pca.limlab.ibms.sinica.edu.tw.

SUBMITTER: Sargsyan K

PROVIDER: S-EPMC3273787 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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GeoPCA: a new tool for multivariate analysis of dihedral angles based on principal component geodesics.

Sargsyan Karen K Wright Jon J Lim Carmay C

Nucleic acids research 20111201 3

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 coordi ...[more]

PMID: 22139913

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