Simulation software tools | Genome-wide association study data analysis
The association analysis between single nucleotide polymorphisms (SNPs) and disease or endpoint in genome-wide association studies (GWAS) has been considered as a powerful strategy for investigating genetic susceptibility and for identifying significant biomarkers. The statistical analysis approaches with simulated data have been widely used to review experimental designs and performance measurements.
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.
Performs stochastic simulations of plant and animal breeding programs. AlphaSimR is the successor to the 'AlphaSim' software for breeding program simulation. Most simulations follow a general structure consisting of four steps: (1) creation of founder haplotypes, (2) setting simulation parameters, (3) modeling of the breeding program, and (4) examination of the results. It contains classes and functions allowing users to simulate a wide range of complex plant and animal breeding programs.
A software tool to add a phenotype to genotypes generated in time-efficient coalescent simulations. Both qualitative and quantitative phenotypes can be generated and it is possible to partition phenotypic variation between additive effects and epistatic interactions between causal variants. The output formats of phenosim are directly usable as input for different GWAS tools. The applicability of phenosim is shown by simulating a genome-wide association study in Arabidopsis thaliana.
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.
A simulation tool that can simulate sequence data with user-specified disease and quantitative trait models. SeqSIMLA can efficiently simulate sequence data with disease or quantitative trait models specified by the user. It is useful for evaluating statistical properties for new study designs and new statistical methods using NGS.