Pedigree generation for analysis of genetic linkage and association.

Journal Article (Journal Article)

We have developed a software package, SIMLA (simulation of linkage and association), which can be used to generate pedigree data under user-specified conditions. The number and location of disease loci, disease penetrances, marker locations, and marker disequilibrium with a disease locus and with other markers can be controlled. In addition, the pedigree size and availability of genotype data may also be specified, and a number of rules for family ascertainment are available. Estimates for power and type I errors can be evaluated under a variety of conditions, as needed by the user. We developed this simulation program because there are no publicly available programs to simulate variable levels of both recombination and linkage disequilibrium (LD) in general pedigrees. Genetic researchers are routinely applying both tests of linkage and family-based tests of association in the search for complex disease genes, and a plethora of different statistical approaches are available. Thus there is a need for the flexible statistical simulation program that we describe. This is the only program that we are aware of that allows simulation of linkage and association for multiple markers in extended pedigrees, nuclear families or in sets of unrelated cases and controls. Furthermore, the program not only allows for variable levels of LD among markers but also between markers and disease loci. SIMLA can simulate the complex and variable levels of LD that have been observed at close markers across the genome and allows for realistic simulation of complex relationships between markers. The program will be useful for studying and comparing existing statistical tests, for developing new genetic linkage and association statistics, planning sample sizes for new studies, and interpreting genetic analysis results.

Full Text

Duke Authors

Cited Authors

  • Bass, MP; Martin, ER; Hauser, ER

Published Date

  • 2004

Published In

  • Pac Symp Biocomput

Start / End Page

  • 93 - 103

PubMed ID

  • 14992495

International Standard Serial Number (ISSN)

  • 2335-6928

Digital Object Identifier (DOI)

  • 10.1142/9789812704856_0010


  • eng

Conference Location

  • United States