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.
References in zbMATH (referenced in 2 articles , 1 standard article )
Showing results 1 to 2 of 2.
- Tayeb, Arafat; Labbe, Aurélie; Bureau, Alexandre; Mérette, Chantal: Solving genetic heterogeneity in extended families by identifying sub-types of complex diseases (2011)
- Schmidt, Mike; Hauser, Elizabeth R.; Martin, Eden R.; Schmidt, Silke: Extension of the SIMLA package for generating pedigrees with complex inheritance patterns: environmental covariates, gene-gene and gene-environment interaction (2005)