The goal of this project is to evaluate statistical genetic methods for detecting, characterizing, and mapping the genes that influence complex diseases and their precursors and risk factors. The investigators will pursue this goal by continuing the organization of the Genetic Analysis Workshops (GAWs). The Genetic Analysis Workshops are a collaborative effort among genetic epidemiologists to evaluate and compare statistical genetic methods. For each GAW, topics are chosen for their relevance to current analytical issues in genetic epidemiology, and sets of computer-simulated or real data are distributed to investigators world-wide. Participants submit the results of their analyses, which are discussed and compared at a 2.5 day meeting. The GAW submissions invariably contain new ideas for methods to handle complex phenotypes. GAW11, held in September 1998, was devoted to problems in genetic analysis of data from the Collaborative Study on the Genetics of Alcoholism and analysis of multiple replicates of simulated data for a multilocus disorder with varying severity and with heterogeneity between populations. GAW11 had 210 participants from the United States, Canada, France, Germany, England, Switzerland, Australia, and Argentina. GAW12 will be held in 2000, and GAW13 in 2002. All planning and data distribution for GAW14 will be essentially complete by the end of the requested period of support in 2004.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
2R01GM031575-17
Application #
2902586
Study Section
Epidemiology and Disease Control Subcommittee 2 (EDC)
Project Start
1983-04-01
Project End
2003-08-31
Budget Start
1999-09-01
Budget End
2000-08-31
Support Year
17
Fiscal Year
1999
Total Cost
Indirect Cost
Name
Southwest Foundation for Biomedical Research
Department
Type
DUNS #
City
San Antonio
State
TX
Country
United States
Zip Code
78245
Wei, Runmin; Wu, Yanyan (2018) Modification effect of fenofibrate therapy, a longitudinal epigenomic-wide methylation study of triglycerides levels in the GOLDN study. BMC Genet 19:75
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Justice, Anne E; Howard, Annie Green; Fernández-Rhodes, Lindsay et al. (2018) Direct and indirect genetic effects on triglycerides through omics and correlated phenotypes. BMC Proc 12:22
Lent, Samantha; Xu, Hanfei; Wang, Lan et al. (2018) Comparison of novel and existing methods for detecting differentially methylated regions. BMC Genet 19:84
Peralta, Juan M; Blackburn, Nicholas B; Porto, Arthur et al. (2018) Genome-wide linkage scan for loci influencing plasma triglyceride levels. BMC Proc 12:52
Gao, Tony Huayang; Zhang, Jianjun; Miguelangel, Diaz Medina et al. (2018) Methods to evaluate rare variants gene-age interaction for triglycerides. BMC Proc 12:49
Wang, Biqi; DeStefano, Anita L; Lin, Honghuang (2018) Integrative methylation score to identify epigenetic modifications associated with lipid changes resulting from fenofibrate treatment in families. BMC Proc 12:28
Fuady, Angga M; Lent, Samantha; Sarnowski, Chloé et al. (2018) Application of novel and existing methods to identify genes with evidence of epigenetic association: results from GAW20. BMC Genet 19:72
Blackburn, Nicholas B; Porto, Arthur; Peralta, Juan M et al. (2018) Heritability and genetic associations of triglyceride and HDL-C levels using pedigree-based and empirical kinships. BMC Proc 12:34

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