The Biostatistics and Bioinformatics Core provides UNC SPORE investigators with support in study design, sampling, data management, and statistical data analysis. The SPORE?s statistical needs are in three primary areas: ongoing data management and analytic support for population-based research; clinical trials; and cDNA microarray studies. Dr. Qaqish, who is expert in sampling design and generalized estimating equations, will oversee the analysis of two, large population science projects (13, 14) and contribute to ongoing data management for Cores 9001 and 9003. A critical component of the statistical support on these projects is taking into account sampling schemes; data management activities include maintenance user support and linkage of laboratory and epidemiologic data. Dr. Michael Schell, who is expert in clinical trials, and monotone regression methods, will provide the leadership for projects 16, 17, 19 and 20. Dr. Yen-Feng Chiu, who is building a career in statistical genetics, will be the lead biostatistician for projects 14 and 18. Dr. David Fenstermacher, a bioinformatics expert and Director of the UNC Bioinformatics Group, will work with Dr. Chiu and a database programmer to support data management and analysis projects using cDNA micorarrays, primarily Project 18 (which, in turn, will inform Project 17, and other projects). The bioinformatics group will use an Oracle database as a component of the GenoMax enterprise software that will be used for many aspects of the microarray data analysis. In addition, programs such as GCG, EMBOSS, Vector NTI Suite II, Paup, and GeneSpring are available through the UNC distributed computing environment. The bioinformatics team will provide the acquisition, storage, linkage and analysis of microarray data that poses both special database and analytic needs due to the extensive volume of data that will be generated. The overall core relies on a host of design and analysis software, including SAS, S-PLUS, StatXact, nQuery Advisor, including both built-in functions and procedures and custom-designed macros and functions. Custom-designed macros that have already been developed include those for reduced monotonic regression, multiple imputation, generalized estimating equations, and the maximal chi-square test.