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.
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Simulates highly divergent DNA sequences and protein superfamilies. iSG is a method for simulating protein sequence evolution and generating realistic protein families. This is accomplished through the addition of subsequence length constraints and lineage- and site-specific evolution. iSG tracks insertion and deletion processes that occur during the simulation run. iSG records all evolutionary events and outputs the "true" multiple alignment of the sequences, and can generate a larger simulated sequence space by allowing the use of multiple related root sequences. iSG can be used to test the accuracy of multiple alignment methods, evolutionary hypotheses, ancestral protein reconstruction methods, and protein superfamily classification methods.
Provides statistical means to infer the strength of association between the rate of sequence evolution in a given genomic region and a phenotype of interest. TraitRateProp is a web server that allows testing the hypothesis of an association between the sequence evolutionary rate and the phenotypic trait. It then computes per-site predictions, where high scores indicate sequence sites whose rate is more likely to be in association with the phenotypic trait. In case where a 3D structure information of the protein is provided, the site-specific scores are mapped onto this structure, thus allowing the detection of putatively functional sequence sites that are spatially close to each other in 3D space.
Simulates multiple nearby disease SNPs on the same chromosome. The new method, HAPGEN2, retains many advantages of resampling methods and expands the range of disease models that current simulators offer.
Aids users to simulate phenotypes and also to evaluate genome-wide association study (GWAS) methods. NaturalGWAS is a simulation model able to incorporate realistic features such as gene-by-environment interactions, where environment is derived from a climate database. This package implements an approach that performs tests using information on confounding variables.
Simulates phenotypes under different models including genetic variant effects and infinitesimal genetic effects, as well as correlated, non-genetic covariates and observational noise effects. PhenotypeSimulator is an R package that combines the phenotype components into a final phenotype while controlling for the proportion of variance explained by each of the components. Users can customize, for each effect component, the number of variables, their distribution and the design of their effect across traits.
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.
Simulates region/gene-level genotype and phenotype data for complex and Mendelian traits for any given pedigree structure. RarePedSim can build conditionally or unconditionally on pedigree members' qualitative or quantitative phenotypes. It employs realistic population demographic models to mimic sequence data. This tool annotates variants sites with positions, allele frequencies and functionalities.
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.
Provides a flexible simulating tool for pathway-based genome-wide association studies using real genetic data from the HapMap project or users. Pathsimu can simultaneously simulate multiple quantitative phenotypes and genome-wide genotype data under users assigned parameters, such as simulation times, genetic models (additive & epistatic genetic models), names or sizes of causal pathways, numbers and genetic effects (main & interactive effects) of disease genes, minor allele frequency ranges of causal SNPs of disease genes. Pathsimu can be used to develop novel multiple gene association study approaches, for instance evaluating the impact of genetic parameters on the power of pathway-based association testing approaches, and comparing the performance of different approaches under various parameter settings. Pathsimu is designed to output data with PLINK file format and be easily extendable.
Reproduces plants breeding strategies exploiting sequence data, pedigrees, genotypes, and phenotypes. AlphaSim is a five-steps package allowing users to specify a wide range of functionalities including the desired recombination rate, model species or Gaussian and Gamma distribution. This application can also be applied for genomic selecting or gene editing and can be run on both short and large datasets.
Simulates realistic samples for genome-wide association studies (GWAS). simuGWAS simulates populations that closely resemble the complex structure of the human genome, while allows the introduction of signals of natural selection. It can simulate realistic samples to evaluate the performance of a wide variety of statistical gene mapping methods for GWAS. Compared to other simulation methods, the tool simulates samples with existing genetic markers that resemble the human populations well in terms of marker allele frequency and linkage disequilibrium (LD) structure, with additional flexibility to simulate genomic regions with signals of natural selection.
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.
Integrates two forms of molecular data with multiple clinical endpoints. CC-PROMISE is an R package that combines canonical correlation (CC), a classical method used to evaluate the association of two multivariate data sets with one another and PROMISE, a method to integrate one form of molecular data with multiple endpoints. The software also includes a probe level analysis.
Aids users in simulating markers that mimic real ones in terms of allele frequencies and linkage disequilibria (LD). DHOEM is a simulation tool that exploits real data characteristics. It has been developed to assist simulation studies in quantitative genetics and selection. This method also allows the user to specify the desired marker density, with a user defined minor allele frequency (MAF) limit.
Allows simulation on population genetic data. GPOPSIM is based on mutation-drift equilibrium (MDE) model. It simulates genetic and phenotypic values for each individual in the current population using the genome structure generated in the historical population, the trait and quantitative trait loci (QTL) parameters. This tool is useful for data simulation in genetic or breeding researches that needs genomic and phenotypic data from a population.
Simulates genomic data with rare variants. SimuRare is a regression-based algorithm imputing rare variants in single nucleotide polymorphism (SNP) array data. It can achieve a resampling approach on any haplotype data to simulate samples including both common and rare SNPs. This method aims to improve realistic linkage disequilibrium (LD) and minor allele frequency (MAFs) maintaining.
A simulation tool for disease/endpoint models of association studies based on single nucleotide polymorphism genotypes. SITDEM is designed to simulate disease/endpoint models based on SNP genotypes.
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.
Assists users for performing simulations using available results of re-sequencing and genomics data. The crossword tool consists of a data-driven simulation language useful for designing genetic-mapping experiments and breeding strategies. This program offers the capability of simulating reads from a genomic sequence generated from a set of individuals in a simulation.
Simulates genome wide associations studies (GWAS) summary data. simGWAS is an R package which can modelize data in the context of case-control studies. The program can be used to reproduce summary data under a specific hypothesis about the location and magnitude of genetic effects or to assess output of fine-mapping applied to real data. It can be applied for any required causal model and set of odds ratios.
Simulates genotype and quantitative trait data in extended pedigrees. SIBSIM is as highly scalable as possible to meet any needs. It may not only be used in simulation studies, but also in the validation, verification and testing process of other applications which deal with the implementation of statistical analysis of genomic data. It had emphasis on the simulation of a quantitative trait in pedigrees of arbitrary size without monozygotic twins.
A simulation based tool, written in the R language that supports power and sample size calculations for stand-alone studies and analyses nested in cohort studies. ESPRESSO enables those designing large cohorts and biobanks to better estimate the sample size required to achieve adequate power. It can also be used to explore specific scientific questions relevant to the design and set up of large-scale association studies and biobanks.
Obsolete
Allows a considerable flexibility in disease models, potentially involving a large number of interacting loci. HAP-SAMPLE is a web application for simulating single nucleotide polymorphism (SNP) genotypes for case-control and affected-child trio studies by resampling from Phase I/II HapMap SNP data. It is a general simulation tool that is immediately available to the research community. The HapMap samples provide limited opportunity for specifying rare disease variants, because of selection bias in HapMap markers and sample size constraints.
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