JSM 2005 - Toronto

Abstract #304294

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 370
Type: Contributed
Date/Time: Wednesday, August 10, 2005 : 8:30 AM to 10:20 AM
Sponsor: Section on Statistical Computing
Abstract - #304294
Title: Bioinformatics Tools for Multivariate u-Statistics Applied to Screening for Genetic Risk Factors of Cardiovascular Diseases
Author(s): Knut M. Wittkowski*+
Companies: The Rockefeller University
Address: General Clinical Research Center, New York, NY, 10021, United States
Keywords:
Abstract:

Common diseases involve multiple outcomes and risk factors. Rank-based methods are more appropriate for nonlinear systems but can be computationally demanding. Traditional multivariate methods based on the linear model define global scores as weighted averages of univariate scores, although the variables' relative importance, correlation, and functional relation with the latent factor are typically unknown. A more efficient approach based on u-statistics overcomes the computational obstacles. For small datasets, spreadsheets can be downloaded (mustat.rockefeller.edu). For larger datasets, data can be uploaded for parallel analysis. We identified genomic pathways in psoriasis (Wittkowski and Lee 2004), gene-gene interaction in addiction (Spangler and Wittkowski 2004), and risk factors for cardiovascular risk (Smith and James 2003). We utilized family data (Trios, Wittkowski and Liu 2002, 2004) and investigated epistasis between diplotypes for their contribution to disease progression and survival. Using the same approach allows for integrating genetic, genomic, proteomic, and phenomic data when screening for interactions.

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Revised March 2005