ArticlePLoS genetics2007
Forward-time simulations of human populations with complex diseases.
Article in PLoS genetics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.
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Who cites it
36 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Genome-wide meta-analysis of common variant differences between men and women.Human molecular genetics · 2012Pooled it
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- Estimating time to the most recent common ancestor (TMRCA): comparison and application of eight methods.European journal of human genetics : EJHG · 2016Article
- A pivot mutation impedes reverse evolution across an adaptive landscape for drug resistance in Plasmodium vivax.Malaria journal · 2016Article
- A Bayesian approach to identify genes and gene-level SNP aggregates in a genetic analysis of cancer data.Statistics and its interface · 2015Article
- ARG-walker: inference of individual specific strengths of meiotic recombination hotspots by population genomics analysis.BMC genomics · 2015Article
- A C++ template library for efficient forward-time population genetic simulation of large populations.Genetics · 2014Article
- Spatial and temporal simulation of human evolution. Methods, frameworks and applications.Current genomics · 2014Article
- 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
- Efficient simulation of epistatic interactions in case-parent trios.Human heredity · 2013Article
- Properties and modeling of GWAS when complex disease risk is due to non-complementing, deleterious mutations in genes of large effect.PLoS genetics · 2013Article
- Using BioBin to explore rare variant population stratification.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2013Article
- Computer programs and methodologies for the simulation of DNA sequence data with recombination.Frontiers in genetics · 2013Article
- BioBin: a bioinformatics tool for automating the binning of rare variants using publicly available biological knowledge.BMC medical genomics · 2013Article
- Simulating gene-gene and gene-environment interactions in complex diseases: Gene-Environment iNteraction Simulator 2.BMC bioinformatics · 2012Article
- Simulation of molecular data under diverse evolutionary scenarios.PLoS computational biology · 2012Article
- Derived SNP alleles are used more frequently than ancestral alleles as risk-associated variants in common human diseases.Journal of bioinformatics and computational biology · 2012Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Due to the increasing power of personal computers, as well as the availability of flexible forward-time simulation programs like simuPOP, it is now possible to simulate the evolution of complex human diseases using a forward-time approach. This approach is potentially more powerful than the coalescent approach since it allows simulations of more than one disease susceptibility locus using almost arbitrary genetic and demographic models. However, the application of such simulations has been deterred by the lack of a suitable simulation framework. For example, it is not clear when and how to introduce disease mutants-especially those under purifying selection-to an evolving population, and how to control the disease allele frequencies at the last generation. In this paper, we introduce a forward-time simulation framework that allows us to generate large multi-generation populations with complex diseases caused by unlinked disease susceptibility loci, according to specified demographic and evolutionary properties. Unrelated individuals, small or large pedigrees can be drawn from the resulting population and provide samples for a wide range of study designs and ascertainment methods. We demonstrate our simulation framework using three examples that map genes associated with affection status, a quantitative trait, and the age of onset of a hypothetical cancer, respectively. Nonadditive fitness models, population structure, and gene-gene interactions are simulated. Case-control, sibpair, and large pedigree samples are drawn from the simulated populations and are examined by a variety of gene-mapping methods.
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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.