JSM 2011 Online Program

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Abstract Details

Activity Number: 359
Type: Contributed
Date/Time: Tuesday, August 2, 2011 : 10:30 AM to 12:20 PM
Sponsor: Biometrics Section
Abstract - #302133
Title: Biomarker Discovery in Lipidomics: A Systematic Comparison of Methods
Author(s): Maiju Elisa Kujala*+
Companies: University of Turku
Address: Assistentinkatu 7, Turun yliopisto, International, 20014, Finland
Keywords: Lipidomics ; variable selection ; biomarker detection
Abstract:

Lipidomic analyses, among other ''omics'' data sets, are becoming a popular part of pharmaceutical drug development. The goal of the present project is to develop statistical methodology for high dimensional and dependent data with real-life applications in lipidomics data sets keeping in mind that methods used should be acceptable both from scientific and regulatory points of view. The current research is a systematic comparison of methods used in biomarker discovery such as stepwise logistic regression, lasso logistic regression, and (regularized) discriminant analysis, among others. The ability of recover structures in these high dimensional data sets is studied by extensive simulations as well as illustrative examples. In addition, special issues such as missing values, sources of variation and respective normalizations and strong correlations between lipids are addresses.


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