Core--Statistical Analysis of Toxics Measurement Data

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This project has two purposes. As the statistics and bioinformatics core, the project will provide statistical and database support to other superfund projects. This will typically involve assistance in experimental design, in the analysis and interpretation of data, in the proposal and development of appropriate statistical methods of data analysis, and in the storage and analysis of microarray, mass spectrometry, and NMR spectroscopy data. In addition, this project proposes the development and refinement of statistical methods and algorithms for the analysis of toxics measurement data, gene expression data, proteomics data, and for the creation of new and improved measurement techniques. A particular emphasis is on the development of new statistical methods for design and analysis of experiments using microarrays (including immunoarrays, DNA arrays, and oligonucleotide arrays), mass spectrometry, and NMR spectroscopy, as well as assisting with the bioinformatics needs associated with these data-intensive methods. We will help deal with such problems as background and baseline correction, peak alignment, compound identification, nonlinear calibration, nonconstant variance, outliers, values near or below detection limits, and high-dimensional and large data sets. Many analytical methods can be made more efficient and effective by careful statistical design and analysis of the data. This may be important to human health, since it allows more frequent monitoring of hazardous sites or for human biomarkers of exposure for the same cost, and since it aids in the development and use of analytical techniques to detect toxic substances both clinically and in the field at lower levels and with greater accuracy than existing methods.