The broad goals are 1. to provide robust, computationally feasible statistical methods for analysis of genetic linkage data, and 2. to analyze the strengths and faults of, improve, and extend existing methods. These should further the goals of locating genetic loci involved in various human traits and diseases, and determine their effects and modes of inheritance.
Specific aims are as follows: A. To develop methods for mapping complex traits by allele-sharing in large pedigrees. Consider selection of most powerful sharing statistics. For multipoint identity-by-descent sharing, make specific proposals regarding properties of such sharing statistics and most powerful statistics under certain assumptions. Develop strategies for fine mapping of complex trait genes in those small isolated founder populations with nearly complete genealogical information, but that are too large for feasible full multipoint analysis. Consider identity-by-state and population association methods and propose strategy to determine most powerful methods under a variety of scenarios. B. To improve assessment of uncertainty in ordering of genetic markers using a robust yet efficient method that does not rely on strong assumptions about interference. Use with Bayesian methods to assess uncertainty, combine data from different studies, integrate maps. C. To develop methods and software for analysis of human sperm data. Implement and improve programs for detecting segregation distortion, modeling interference, and for robust marker ordering with sperm data. Use these implementations to study heterogeneity of genetic parameters in human males. D. To investigate robustness of linkage procedures to problems such as misspecified allele frequencies, genotyping errors, and interference. Study role of incomplete data in exacerbating misspecification problems. Pinpoint areas of greatest concern, develop diagnostics and remedies.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
First Independent Research Support & Transition (FIRST) Awards (R29)
Project #
5R29HG001645-02
Application #
2674264
Study Section
Special Emphasis Panel (ZRG2-GNM (04))
Project Start
1997-09-01
Project End
2002-08-31
Budget Start
1998-09-01
Budget End
1999-08-31
Support Year
2
Fiscal Year
1998
Total Cost
Indirect Cost
Name
University of Chicago
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
225410919
City
Chicago
State
IL
Country
United States
Zip Code
60637