The Human Genome Project is providing outstanding resources for the identification of genes that predispose to human diseases: more and better genetic markers, a burgeoning catalog of human sequence variation, a draft sequence of the human genome, and increasingly detailed annotation of the sequence with genes and ESTs. These resources will be critical as we seek to unravel the complex etiologic basis of common human diseases. In this proposal, I address a set of statistical problems that arise in human disease gene mapping. I describe how my colleagues and I will address these problems through analytic methods and computer simulation, and how we will generalize these solutions through the production and distribution of efficient computer software. First, we will carry out statistical design and analysis work to establish the utility and permit the use of an experimental method for haplotype determination called conversion in linkage disequilibrium and linkage studies. We will assess efficiency, develop statistical algorithms to construct haplotypes from conversion-based genotype data, and develop methods and algorithms required for statistical analysis. Second, we will continue to develop and test methods for linkage mapping of genes for complex human diseases. We will: develop methods to minimize etiologic heterogeneity; build a framework for mapping complex and quantitative traits based on the generalized linear mixed model; continue to investigate issues of data quality in gene mapping studies; and address issues in localizing genes for complex human diseases when combining data from several different genome scans. Third, we will develop, test, distribute, and support computer software based on the methods that arise from the other goals of this project, and will continue to update, distribute, and support our current software, including SIMLINK, RHMAP, RELPAIR, SIBMED, and several modules of the MENDEL package. Finally, we will continue to be opportunistic in identifying and addressing important statistical modeling and analysis problems that are related to the other goals of this project.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Research Project (R01)
Project #
5R01HG000376-17
Application #
6797185
Study Section
Genome Study Section (GNM)
Program Officer
Brooks, Lisa
Project Start
1988-09-28
Project End
2005-08-31
Budget Start
2004-09-01
Budget End
2005-08-31
Support Year
17
Fiscal Year
2004
Total Cost
$303,752
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Schools of Public Health
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
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