Methods for Analysis of High Throughput Assay Data

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DESCRIPTION (provided by applicant): The main goal of this project is to develop methods of analysis and software implementations for gene expression data, proteomics data, and metabolomics data that are informed by research on the statistical characteristics of the data that are to be analyzed. The principles guiding this methods-development project include the following: 1) high-throughput assay data require transformation so that measurements can be treated in the same fashion across the full range; 2) linear statistical models provide a powerful class of methods that are often sufficient to address the real biological problems at issue (though nonlinear models should be available when required); 3) statistical tests should use appropriate comparison standards so that the tests achieve the highest power consistent with preventing excessive false positives. Under this proposal, we will continue the development of methods and software for gene expression data, and carry over the methods to the analysis of proteomics and metabolomics data by mass spectrometry and NMR spectroscopy.