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A Novel Bayesian Change-point Algorithm for Genome-wide Analysis of Diverse ChIPseq Data Types
Published on: December 10, 2012
A new proposal for a principal component-based test for high-dimensional data applied to the analysis of PhyloChip
Guo-Chun Ding1, Kornelia Smalla, Holger Heuer
1Institute for Epidemiology and Pathogen Diagnostics, Julius Kühn-Institut, Messeweg 11-12, 38104, Braunschweig, Germany.
Abstract:
A modification of the principal component test is presented. It uses a weighted combination of the sums of squares for different principal components and is thus more powerful in high-dimensional settings with small sample sizes. Under usual normality assumptions, a rotation test is proposed which enables an exact conditional parametric test. The procedure is demonstrated with microarray data for the bacterial composition in the rhizosphere of different potato cultivars. In simulation studies, the power of the proposed statistic is compared with the competing multivariate parametric tests.
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