Abstract

The long-term goal is to develop novel analytical methods that will enable researchers to find sets of disease genes underlying complex traits. These methods make use of genetic linkage and linkage disequilibrium between markers and nearby disease genes and provide, for example, maximum likelihood estimates for the numbers and positions of disease genes. Results are expected to open the way to identifying susceptibility genes. Once such genes are found, there is hope that knowledge of their structure will lead to a deeper understanding of disease etiology and, thus, to the possibility of ameliorating or curing these traits. The three specific aims are 1) to apply the Ising model of statistical physics to linkage and disequilibrium analysis, 2) to investigate effects of pedigree errors on disequilibrium analysis, and 3) to implement methodology developed under this proposal in computer programs.

  Funding Agency

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
1R01MH059492-01A1
Application #
6053050
Study Section
Mammalian Genetics Study Section (MGN)
Program Officer
Moldin, Steven Owen
Project Start
2000-03-01
Project End
2003-02-28
Budget Start
2000-03-01
Budget End
2001-02-28
Support Year
1
Fiscal Year
2000
Total Cost
$137,785
Indirect Cost

  Institution

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

  Publications

Xu, Jinfeng; Yang, Yaning; Ying, Zhiliang et al. (2008) Testing linkage disequilibrium from pooled DNA: a contingency table perspective. Stat Med 27:5801-15
Kang, S J; Gordon, D; Brown, A M et al. (2004) Tradeoff between no-call reduction in genotyping error rate and loss of sample size for genetic case/control association studies. Pac Symp Biocomput :116-27
Gordon, Derek; Haynes, Chad; Johnnidis, Christopher et al. (2004) A transmission disequilibrium test for general pedigrees that is robust to the presence of random genotyping errors and any number of untyped parents. Eur J Hum Genet 12:752-61
Kang, Sun Jung; Gordon, Derek; Finch, Stephen J (2004) What SNP genotyping errors are most costly for genetic association studies? Genet Epidemiol 26:132-41
Martinez-Mir, Amalia; Zlotogorski, Abraham; Ott, Jurg et al. (2003) Genetic linkage studies in alopecia areata. J Investig Dermatol Symp Proc 8:199-203
Gordon, D; Levenstien, M A; Finch, S J et al. (2003) Errors and linkage disequilibrium interact multiplicatively when computing sample sizes for genetic case-control association studies. Pac Symp Biocomput :490-501
Hoh, Josephine; Matsuda, Fumihiko; Peng, Xu et al. (2003) SNP haplotype tagging from DNA pools of two individuals. BMC Bioinformatics 4:14
Levenstien, Mark A; Yang, Yaning; Ott, Jurg (2003) Statistical significance for hierarchical clustering in genetic association and microarray expression studies. BMC Bioinformatics 4:62
Liu, Xin; Gordon, Derek (2003) A general class of association tests for family-based data using weight functions. Genet Epidemiol 24:208-19
Martinez-Mir, A; Zlotogorski, A; Londono, D et al. (2003) Identification of a locus for type I punctate palmoplantar keratoderma on chromosome 15q22-q24. J Med Genet 40:872-8

Showing the most recent 10 out of 17 publications