Simulation software tools | Genome-wide association study data analysis

Simulates multiple nearby disease single nucleotide positions (SNPs) on the same chromosome. HAPGEN is based on an alternative resampling method that uses a reference panel of haplotypes to generate a sample with patterns of linkage disequilibrium (LD) similar to those in the reference panel. It aims to be useful for searching disease models involving multiple disease SNPs within close proximity.

Generates data sets of families for use in Linkage and Association studies. SIMLA allows the user flexibility in specifying marker and disease placement, locus heterogeneity, disequilibrium between markers and disease loci. It allows simulation of linkage and association for multiple markers in extended pedigrees, nuclear families or in sets of unrelated cases and controls. 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.

Mimics highly divergent DNA sequences and protein superfamilies. iSG simulates protein sequence evolution and builds realistic protein families. It utilizes multiple related root sequences to construct large simulated sequence space. This tool implements subsequence length constraints and lineage- and site-specific evolution. It is useful for testing the accuracy of multiple alignment methods or evolutionary hypotheses.

A rapid moving-window algorithm to simulate genotype data for case-control or population samples from genomic SNP chips. For case-control data, GWAsimulator generates cases and controls according to a user-specified multi-locus disease model, and can simulate specific regions if desired. The program uses phased genotype data as input and has the flexibility of simulating genotypes for different populations and different genomic SNP chips.

Generates complex biallelic single nucleotide polymorphism (SNP) disease models for simulation studies. GAMETES rapidly and precisely generates random, pure, strict n-locus models with specified genetic constraints. It includes a simple dataset simulation strategy which may be utilized to rapidly generate an archive of simulated datasets for given genetic models. The tool could be employed to pursue theoretical characterization of genetic models and epistasis.