Literature DB >> 16646832

Extension of the SIMLA package for generating pedigrees with complex inheritance patterns: environmental covariates, gene-gene and gene-environment interaction.

Mike Schmidt1, Elizabeth R Hauser, Eden R Martin, Silke Schmidt.   

Abstract

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.

Entities:  

Year:  2005        PMID: 16646832      PMCID: PMC1403827          DOI: 10.2202/1544-6115.1133

Source DB:  PubMed          Journal:  Stat Appl Genet Mol Biol        ISSN: 1544-6115


  16 in total

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2.  Genotype-based association test for general pedigrees: the genotype-PDT.

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Journal:  Genet Epidemiol       Date:  2003-11       Impact factor: 2.135

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Authors:  Elizabeth R Hauser; Richard M Watanabe; William L Duren; Meredyth P Bass; Carl D Langefeld; Michael Boehnke
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4.  Pedigree generation for analysis of genetic linkage and association.

Authors:  M P Bass; E R Martin; E R Hauser
Journal:  Pac Symp Biocomput       Date:  2004

5.  Mega2: data-handling for facilitating genetic linkage and association analyses.

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6.  Linkage disequilibrium inflates type I error rates in multipoint linkage analysis when parental genotypes are missing.

Authors:  Abee L Boyles; William K Scott; Eden R Martin; Silke Schmidt; Yi-Ju Li; Allison Ashley-Koch; Meredyth P Bass; Michael Schmidt; Margaret A Pericak-Vance; Marcy C Speer; Elizabeth R Hauser
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Authors:  E R Hauser; M Boehnke
Journal:  Biometrics       Date:  1998-12       Impact factor: 2.571

8.  Estimating the power of a proposed linkage study for a complex genetic trait.

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10.  Estimating the power of a proposed linkage study: a practical computer simulation approach.

Authors:  M Boehnke
Journal:  Am J Hum Genet       Date:  1986-10       Impact factor: 11.025

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  28 in total

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5.  Ordered-subset analysis (OSA) for family-based association mapping of complex traits.

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Journal:  Genet Epidemiol       Date:  2008-11       Impact factor: 2.135

6.  Coordinated conditional simulation with SLINK and SUP of many markers linked or associated to a trait in large pedigrees.

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7.  A general framework for formal tests of interaction after exhaustive search methods with applications to MDR and MDR-PDT.

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8.  Multifactor dimensionality reduction-phenomics: a novel method to capture genetic heterogeneity with use of phenotypic variables.

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9.  A cross-validation procedure for general pedigrees and matched odds ratio fitness metric implemented for the multifactor dimensionality reduction pedigree disequilibrium test.

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10.  A novel approach to simulate gene-environment interactions in complex diseases.

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