Parametric linkage models, when carefully applied, can be invaluable in unraveling the complexities of interacting genes in complex diseases. The investigators will develop a faster likelihood engine using novel algorithms to extend the range of possible applications of parametric linkage analysis to include multilocus models to measure interaction between susceptibility genes and regressive models to be able to account for covariates, environmental factors, and familial correlations. Haplotype variation analysis is a very powerful approach to measure the variation of quantitative traits and to aid in their fine mapping. The investigators will develop zero-recombinant haplotype programs to efficiently carry out this analysis. The haplotype program will be particularly useful as array technologies begin to permit rapid genotyping at thousands of single nucleotide polymorphism markers. Simulation is an integral part in many non-parametric approaches and for testing the power of statistical models used in the study of complex diseases. A robust simulation engine based on the faster likelihood engine will be developed by the investigators. The algorithms will be implemented in VITESSE to develop an integrated package for the study of complex diseases using more powerful parametric models. The investigators will rigorously test and validate the computational and simulation engine and haplotyping programs to ensure correctness of the algorithms. They will also optimize the code to run efficiently on all platforms in general use by other researchers. The investigators will document and distribute the programs via the Internet to the worldwide scientific community.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Research Project (R01)
Project #
5R01AG016992-02
Application #
6043142
Study Section
Special Emphasis Panel (ZRG2-GNM (02))
Program Officer
Mccormick, Anna M
Project Start
1998-09-30
Project End
2001-07-31
Budget Start
1999-09-01
Budget End
2000-07-31
Support Year
2
Fiscal Year
1999
Total Cost
Indirect Cost
Name
University of Pittsburgh
Department
Genetics
Type
Schools of Public Health
DUNS #
053785812
City
Pittsburgh
State
PA
Country
United States
Zip Code
15213
Mukhopadhyay, Nandita; Almasy, Lee; Schroeder, Mark et al. (2005) Mega2: data-handling for facilitating genetic linkage and association analyses. Bioinformatics 21:2556-7
Jan De Beur, Suzanne M; O'Connell, Jeffery R; Peila, Rita et al. (2003) The pseudohypoparathyroidism type lb locus is linked to a region including GNAS1 at 20q13.3. J Bone Miner Res 18:424-33
Shugart, Yin Yao; O'Connell, Jeffrey R; Wilson, Alexander F (2002) An evaluation of the variance components approach: type I error, power and size of the estimated effect. Eur J Hum Genet 10:133-6
O'Connell, J R (2001) Rapid multipoint linkage analysis via inheritance vectors in the Elston-Stewart algorithm. Hum Hered 51:226-40
Hart, T C; Pallos, D; Bozzo, L et al. (2000) Evidence of genetic heterogeneity for hereditary gingival fibromatosis. J Dent Res 79:1758-64
O'Connell, J R (2000) Zero-recombinant haplotyping: applications to fine mapping using SNPs. Genet Epidemiol 19 Suppl 1:S64-70
O'Connell, J R; Weeks, D E (1999) An optimal algorithm for automatic genotype elimination. Am J Hum Genet 65:1733-40