A number of statistical methods have been developed for analyzing family and population data to detect and characterize the genetic contribution to common diseases and their risk factors. These methods include complex segregation analysis, linkage analysis, variance components analysis, path analysis, and various exploratory methods. The goal of this project is to evaluate the strengths and limitations of these methods. This goal will be pursued by: (1) Organizing Genetic Analysis Workshops in 1987, 1988 and 1990. For each Workshop, sets of data, either computer-simulated or real, will be distributed to investigators worldwide. Results of analyses will be discussed and compared at a two day meeting of Workshop participants, and a summary will be presented at the American Society of Human Genetics meetings. (2) Conducting evaluations of power, specificity, and robustness of methods of genetic analysis. Topics to be addressed include (a) evaluation of methods for resolving the order of linked marker loci; (b) development of methods for evaluating the informativeness of family data for linkage studies; (c) evaluation of methods of quantitative linkage analysis; (d) interpretation of skewness in quantitative traits; (e) detecting major genes for dichotomous traits; (f) detecting the contribution of two or more major loci; and (g) studying disease liability through a correlated trait. Byproducts of this project will include (1) a set of transportable computer programs that will facilitate the use of some of the more commonly applied genetic analysis programs, and (2) a package of computer simulation programs that will facilitate evaluation of genetic epidemiological methods.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM031575-07
Application #
3279699
Study Section
Epidemiology and Disease Control Subcommittee 3 (EDC)
Project Start
1983-04-01
Project End
1991-03-31
Budget Start
1989-04-01
Budget End
1990-03-31
Support Year
7
Fiscal Year
1989
Total Cost
Indirect Cost
Name
Southwest Foundation for Biomedical Research
Department
Type
DUNS #
City
San Antonio
State
TX
Country
United States
Zip Code
78245
Romanescu, Razvan G; Espin-Garcia, Osvaldo; Ma, Jin et al. (2018) Integrating epigenetic, genetic, and phenotypic data to uncover gene-region associations with triglycerides in the GOLDN study. BMC Proc 12:57
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Lent, Samantha; Xu, Hanfei; Wang, Lan et al. (2018) Comparison of novel and existing methods for detecting differentially methylated regions. BMC Genet 19:84

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