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Publication Date:
June 2005
ISSN:
1544-6115
DOI:
10.2202/1544-6115.1133

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Editor-in-Chief: Stumpf, Michael P.H.

Editorial Board Member: Beaumont, Mark / Binder, Harald / Gupta, Mayetri / Hubbard, Alan E. / Husmeier, Dirk / Ji, Hongkai / Keles, Sunduz / Kerr, Kathleen / Lazzeroni, Laura / Lin, Shili / Ma, Ping / Marjoram, Paul / Mertens, Bart / Nerman, Olle / G. Petretto, Enrico / Plagnol, Vincent / Purdom, Elizabeth / Robin, Stéphane / Rzhetsky, Andrey / Sanguinetti, Guido / van der Laan, Mark J. / von Haeseler, Arndt / Weeks, Daniel E. / Wiuf, Carsten / Zhao, Hongyu

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IMPACT FACTOR 2011: 1.517
5-year IMPACT FACTOR: 1.704
Rank 27 out of 116 in category Statistics & Probability in the 2011 Thomson Reuters Journal Citation Report/Science Edition

Extension of the SIMLA Package for Generating Pedigrees with Complex Inheritance Patterns: Environmental Covariates, Gene-Gene and Gene-Environment Interaction

Mike Schmidt / Elizabeth R Hauser / Eden R. Martin / Silke Schmidt

1Center for Human Genetics, Duke University Medical Center

1Center for Human Genetics, Duke University Medical Center

1Center for Human Genetics, Duke University Medical Center

1Center for Human Genetics, Duke University Medical Center

Citation Information: Statistical Applications in Genetics and Molecular Biology. Volume 4, Issue 1, Pages –, ISSN (Online) 1544-6115, DOI: 10.2202/1544-6115.1133, June 2005

Publication History:
Published Online:
2005-06-06

We have previously distributed a software package, SIMLA (SIMulation of Linkage and Association), which can be used to generate disease phenotype and marker genotype data in three-generational pedigrees of user-specified structure. To our knowledge, SIMLA is the only publicly available program that can simulate variable levels of both linkage (recombination) and linkage disequilibrium (LD) between marker and disease loci in general pedigrees. While the previous SIMLA version provided flexibility in choosing many parameters relevant for linkage and association mapping of complex human diseases, it did not allow for the segregation of more than one disease locus in a given pedigree and did not incorporate environmental covariates possibly interacting with disease susceptibility genes.Here, we present an extension of the simulation algorithm characterized by a much more general penetrance function, which allows for the joint action of up to two genes and up to two environmental covariates in the simulated pedigrees, with all possible multiplicative interaction effects between them. This makes the program even more useful for comparing the performance of different linkage and association analysis methods applied to complex human phenotypes. SIMLA can assist investigators in planning and designing a variety of linkage and association studies, and can help interpret results of real data analyses by comparing them to results obtained under a user-controlled data generation mechanism.A free download of the SIMLA package is available at http://wwwchg.duhs.duke.edu/software.

Keywords: genetics; statistics; software; linkage; association

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