VizStruct

MOTIVATION: The size, dimensionality and the limited range of the data values
make visualization of single nucleotide polymorphism (SNP) datasets challenging.
The purpose of this study is to evaluate the usefulness of 3D VizStruct, a novel
multi-dimensional data visualization technique for analyzing patterns in SNP
datasets. RESULTS: VizStruct is an interactive visualization technique that
reduces multi-dimensional data to two dimensions using the complex-valued
harmonics of the discrete Fourier transform (DFT). In the 3D VizStruct extension,
the multi-dimensional SNP data vectors are reduced to three dimensions using a
combination of the DFT and the Kullback-Leibler divergence. The performance of 3D
VizStruct was challenged with several biologically relevant published datasets
that included human Chromosome 21, the human lipoprotein lipase (LPL) gene locus
and the multi-locus genotypes of coral populations. In every case, the 3D
VizStruct mapping provided an intuitive visual description of the key
characteristics of the underlying multi-dimensional genotype.

VizStruct for visualization of genome-wide SNP analyses.

VizStruct is a web-based service to visualize gene expression profiling. The VizStruct algorithm uses the complex-valued harmonics of the discrete Fourier transform (DFT) method to reduce multi-dimensional data into two dimensions.

VizStruct

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