Complex genetic traits are those whose pattern of inheritance does not follow Mendelian patterns, due to decreased penetrance and multiple, interacting genes influencing the trait. As many common inherited diseases show complex patterns of inheritance, methods for finding the genes underlying complex genetic traits is especially important in human genetics. This problem is particularly pronounced when epistasis (gene interaction) is taken into account. Two approaches to this problem are scanning markers across the whole genome for association with the disease and first using functional analysis to generate a list of candidate genes before testing for association. The performance of current methods for doing association studies, which generally look at one locus at a time, will be assessed under models of epistasis. The technique of market basket analysis from computer science will be applied to find genotypes associated with disease state. Finally, the same market basket analysis algorithm will be applied to gene expression data. This will generate lists of genes whose expression appears to be associated with each other or with a tissue or condition of interest.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
1F32HG003681-01
Application #
6938220
Study Section
Special Emphasis Panel (ZRG1-F08 (20))
Program Officer
Graham, Bettie
Project Start
2005-05-18
Project End
2008-05-17
Budget Start
2005-05-18
Budget End
2006-05-17
Support Year
1
Fiscal Year
2005
Total Cost
$43,976
Indirect Cost
Name
Rockefeller University
Department
Biostatistics & Other Math Sci
Type
Other Domestic Higher Education
DUNS #
071037113
City
New York
State
NY
Country
United States
Zip Code
10065