SeqSIMLA
SeqSIMLA simulates sequence data for family-based and case-control genetic studies, enabling modeling of complex familial relationships and shared environmental influences on disease and quantitative traits.
Key Features:
- Simulation of Family and Case-Control Data: Generates sequence data for unrelated cases and controls as well as for pedigrees with multiple affected and unaffected siblings across disease models and quantitative trait scenarios.
- Modeling Shared Environmental Effects: Explicitly incorporates shared environmental effects among relatives to capture familial clustering of traits such as body mass index.
- Flexible Pedigree Structures: Simulates prespecified pedigree structures without restrictions on the number of individuals per pedigree, supporting large and complex pedigrees.
- Correlated Traits Simulation: Simulates correlated traits and realistic correlation structures between related phenotypes, for example systolic and diastolic blood pressure among relatives.
- Efficiency in Large-Scale Simulations: Optimized to simulate large pedigrees and extensive chromosomal regions within reasonable timeframes for high-throughput genetic studies.
Scientific Applications:
- Power Evaluation: Evaluating statistical power to detect causal variants in planned family-based and case-control studies.
- Method Assessment: Assessing statistical properties and performance of novel analytical methods for complex trait analysis.
- Study Design and Interpretation: Designing experiments and interpreting results that involve interacting genetic and environmental influences within family structures.
Methodology:
Simulates sequence data for unrelated individuals and pedigrees, incorporates shared environmental effects among relatives, generates prespecified pedigree structures of arbitrary size, simulates correlated traits, and models extensive chromosomal regions for large-scale simulations.
Topics
Details
- Tool Type:
- command-line tool, web application
- Operating Systems:
- Linux, Windows, Mac
- Programming Languages:
- C++
- Added:
- 8/3/2017
- Last Updated:
- 11/25/2024
Operations
Publications
Chung R, Tsai W, Hsieh C, Hung K, Hsiung CA, Hauser ER. SeqSIMLA2: Simulating Correlated Quantitative Traits Accounting for Shared Environmental Effects in User‐Specified Pedigree Structure. Genetic Epidemiology. 2014;39(1):20-24. doi:10.1002/gepi.21850. PMID:25250827.