ArticleBMC bioinformatics2010
Forward-time simulation of realistic samples for genome-wide association studies.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 39 citations in OpenAlex.
- Establishing standards for genome wide association studies in eusocial insects through a case study in honey bees.Scientific reports · 2026Article
- HAP-SAMPLE2: data-based resampling for association studies with admixture.Bioinformatics (Oxford, England) · 2025Article
- Refining the scope of genetic influences on alcohol misuse through environmental stratification and gene-environment interaction.Alcohol, clinical & experimental research · 2024Article
- Prospects for genomic surveillance for selection in schistosome parasites.Frontiers in epidemiology · 2022Review
- Fast and Accurate Shared Segment Detection and Relatedness Estimation in Un-phased Genetic Data via TRUFFLE.American journal of human genetics · 2019Article
- sim1000G: a user-friendly genetic variant simulator in R for unrelated individuals and family-based designs.BMC bioinformatics · 2019Article
- Simulating variance heterogeneity in quantitative genome wide association studies.BMC bioinformatics · 2018Article
- Reproducible simulations of realistic samples for next-generation sequencing studies using Variant Simulation Tools.Genetic epidemiology · 2015Article
- A whole-genome simulator capable of modeling high-order epistasis for complex disease.Genetic epidemiology · 2013Article
- Genomic prediction in animals and plants: simulation of data, validation, reporting, and benchmarking.Genetics · 2013Review
- Simulating realistic genomic data with rare variants.Genetic epidemiology · 2013Article
- Simulating gene-gene and gene-environment interactions in complex diseases: Gene-Environment iNteraction Simulator 2.BMC bioinformatics · 2012Article
- Inferring coancestry in population samples in the presence of linkage disequilibrium.Genetics · 2012Article
- SHIPS: Spectral Hierarchical clustering for the Inference of Population Structure in genetic studies.PloS one · 2012Article
- Parameters in dynamic models of complex traits are containers of missing heritability.PLoS computational biology · 2012Article
- phenosim--A software to simulate phenotypes for testing in genome-wide association studies.BMC bioinformatics · 2011Article
- Simulating linkage disequilibrium structures in a human population for SNP association studies.Biochemical genetics · 2011Article
- Accounting for population stratification in practice: a comparison of the main strategies dedicated to genome-wide association studies.PloS one · 2011Article
- Simulating sequences of the human genome with rare variants.Human heredity · 2010Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
backgroundForward-time simulations have unique advantages in power and flexibility for the simulation of genetic samples of complex human diseases because they can closely mimic the evolution of human populations carrying these diseases. However, a number of methodological and computational constraints have prevented the power of this simulation method from being fully explored in existing forward-time simulation methods.
resultsUsing a general-purpose forward-time population genetics simulation environment, we developed a forward-time simulation method that can be used to simulate realistic samples for genome-wide association studies. We examined the properties of this simulation method by comparing simulated samples with real data and demonstrated its wide applicability using four examples, including a simulation of case-control samples with a disease caused by multiple interacting genetic and environmental factors, a simulation of trio families affected by a disease-predisposing allele that had been subjected to either slow or rapid selective sweep, and a simulation of a structured population resulting from recent population admixture.
conclusionsOur algorithm simulates populations that closely resemble the complex structure of the human genome, while allows the introduction of signals of natural selection. Because of its flexibility to generate different types of samples with arbitrary disease or quantitative trait models, this simulation method can simulate realistic samples to evaluate the performance of a wide variety of statistical gene mapping methods for genome-wide association studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.