Generating linkage disequilibrium patterns in data simulations using genomeSIMLA

Todd L. Edwards; William S. Bush; Stephen D. Turner; Scott M. Dudek; Eric S. Torstenson; Mike Schmidt; Eden Martin; Marylyn D. Ritchie

doi:10.1007/978-3-540-78757-0_3

Generating linkage disequilibrium patterns in data simulations using genomeSIMLA

Todd L. Edwards, William S. Bush, Stephen D. Turner, Scott M. Dudek, Eric S. Torstenson, Mike Schmidt, Eden Martin, Marylyn D. Ritchie

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

39 Scopus citations

Abstract

Whole-genome association (WGA) studies are becoming a common tool for the exploration of the genetic components of common disease. The analysis of such large scale data presents unique analytical challenges, including problems of multiple testing, correlated independent variables, and large multivariate model spaces. These issues have prompted the development of novel computational approaches. Thorough, extensive simulation studies are a necessity for methods development work to evaluate the power and validity of novel approaches. Many data simulation packages exist, however, the resulting data is often overly simplistic and does not compare to the complexity of real data; especially with respect to linkage disequilibrium (LD). To overcome this limitation, we have developed genomeSIMLA. GenomeSIMLA is a forward-time population simulation method that can simulate realistic patterns of LD in both family-based and case-control datasets. In this manuscript, we demonstrate how LD patterns of the simulated data change under different population growth curve parameter initialization settings. These results provide guidelines to simulate WGA datasets whose properties resemble the HapMap.

Original language	English (US)
Title of host publication	Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 6th European Conference, EvoBIO 2008, Proceedings
Pages	24-35
Number of pages	12
DOIs	https://doi.org/10.1007/978-3-540-78757-0_3
State	Published - Jul 21 2008
Event	6th European Conference on Evolutionary Computation, Machine Learning, and Data Mining in Bioinformatics, EvoBIO 2008 - Naples, Italy Duration: Mar 26 2008 → Mar 28 2008

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	4973 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Other

Other	6th European Conference on Evolutionary Computation, Machine Learning, and Data Mining in Bioinformatics, EvoBIO 2008
Country	Italy
City	Naples
Period	3/26/08 → 3/28/08

Keywords

Data simulation
Linkage disequilibrium
Whole genome association

ASJC Scopus subject areas

Computer Science(all)
Biochemistry, Genetics and Molecular Biology(all)
Theoretical Computer Science

Access to Document

10.1007/978-3-540-78757-0_3

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Edwards, T. L., Bush, W. S., Turner, S. D., Dudek, S. M., Torstenson, E. S., Schmidt, M., Martin, E., & Ritchie, M. D. (2008). Generating linkage disequilibrium patterns in data simulations using genomeSIMLA. In Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 6th European Conference, EvoBIO 2008, Proceedings (pp. 24-35). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4973 LNCS). https://doi.org/10.1007/978-3-540-78757-0_3

Generating linkage disequilibrium patterns in data simulations using genomeSIMLA. / Edwards, Todd L.; Bush, William S.; Turner, Stephen D.; Dudek, Scott M.; Torstenson, Eric S.; Schmidt, Mike ; Martin, Eden; Ritchie, Marylyn D.

Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 6th European Conference, EvoBIO 2008, Proceedings. 2008. p. 24-35 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4973 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Edwards, TL, Bush, WS, Turner, SD, Dudek, SM, Torstenson, ES, Schmidt, M , Martin, E & Ritchie, MD 2008, Generating linkage disequilibrium patterns in data simulations using genomeSIMLA. in Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 6th European Conference, EvoBIO 2008, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 4973 LNCS, pp. 24-35, 6th European Conference on Evolutionary Computation, Machine Learning, and Data Mining in Bioinformatics, EvoBIO 2008, Naples, Italy, 3/26/08. https://doi.org/10.1007/978-3-540-78757-0_3

Edwards TL, Bush WS, Turner SD, Dudek SM, Torstenson ES, Schmidt M et al. Generating linkage disequilibrium patterns in data simulations using genomeSIMLA. In Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 6th European Conference, EvoBIO 2008, Proceedings. 2008. p. 24-35. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-540-78757-0_3

Edwards, Todd L. ; Bush, William S. ; Turner, Stephen D. ; Dudek, Scott M. ; Torstenson, Eric S. ; Schmidt, Mike ; Martin, Eden ; Ritchie, Marylyn D. / Generating linkage disequilibrium patterns in data simulations using genomeSIMLA. Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 6th European Conference, EvoBIO 2008, Proceedings. 2008. pp. 24-35 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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