ArticleAmerican journal of human genetics2005
In silico analysis of disease-association mapping strategies using the coalescent process and incorporating ascertainment and selection.
Article in American journal of human genetics, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
6 citing papers in PubMed, 23 citations in OpenAlex.
- An overview of population genetic data simulation.Journal of computational biology : a journal of computational molecular cell biology · 2012Review
- Forward-time simulation of realistic samples for genome-wide association studies.BMC bioinformatics · 2010Article
- A radiation-derived gene expression signature predicts clinical outcome for breast cancer patients.Radiation research · 2009Article
- Bayesian inference of population size history from multiple loci.BMC evolutionary biology · 2008Article
- A survey of genetic simulation software for population and epidemiological studies.Human genomics · 2008Review
- Forward-time simulations of human populations with complex diseases.PLoS genetics · 2007Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
Abstract
We present a new method for simulating samples of marker haplotypes, genotypes, or diplotypes in case-control studies in which the markers are linked to a disease locus in any specified region of the genome. The method allows realistic features to be incorporated into the simulations, including selection acting on disease alleles, sample ascertainment of disease chromosomes and polymorphic markers, a genetic dominance model of disease expression that allows incomplete penetrance and phenocopies, and an accurate genetic map of recombination rates and hotspots for recombination in the human genome (or, alternatively, an improved method for simulating the distribution of hotspots). The new method uses an approach that combines simulation of the coalescent process for the sampled chromosomes with a diffusion process used to model the evolution of the disease-mutation frequency over time. Examples illustrate how the method may be used to study the expected power of a marker-disease association study.
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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.