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 proceedingConference contribution

38 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 languageEnglish (US)
Title of host publicationEvolutionary Computation, Machine Learning and Data Mining in Bioinformatics - 6th European Conference, EvoBIO 2008, Proceedings
Pages24-35
Number of pages12
DOIs
StatePublished - Jul 21 2008
Event6th European Conference on Evolutionary Computation, Machine Learning, and Data Mining in Bioinformatics, EvoBIO 2008 - Naples, Italy
Duration: Mar 26 2008Mar 28 2008

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4973 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th European Conference on Evolutionary Computation, Machine Learning, and Data Mining in Bioinformatics, EvoBIO 2008
CountryItaly
CityNaples
Period3/26/083/28/08

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All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

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