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Approximate Bayesian computation in population genetics.
A key advantage of the method is that the nuisance parameters are automatically integrated out in the simulation step, so that the large numbers of nuisance parameters that arise in population genetics problems can be handled without difficulty.
A genome-wide association study identifies novel risk loci for type 2 diabetes
Four loci containing variants that confer type 2 diabetes risk are identified and constitute proof of principle for the genome-wide approach to the elucidation of complex genetic traits.
Inferring population history with DIY ABC: a user-friendly approach to approximate Bayesian computation
Key methods used in DIY ABC, a computer program for inference based on approximate Bayesian computation (ABC), in which scenarios can be customized by the user to fit many complex situations involving any number of populations and samples, are described.
Identifying adaptive genetic divergence among populations from genome scans
A hierarchical‐Bayesian method is developed, implemented via Markov chain Monte Carlo (MCMC), and its performance is assessed in distinguishing the loci simulated under selection from the neutral loci, finding that both methods can identify loci subject to adaptive selection when the selection coefficient is at least five times the migration rate.
A tutorial on statistical methods for population association studies
- D. Balding
- BiologyNature Reviews Genetics
- 1 October 2006
An overview of statistical approaches to population association studies, including preliminary analyses (Hardy–Weinberg equilibrium testing, inference of phase and missing data, and SNP tagging), and single-SNP and multipoint tests for association.
Inferring coalescence times from DNA sequence data.
Extensions are presented that allow for the effects of uncertainty in knowledge of population size and mutation rates, for variability in population sizes, for regions of different mutation rate, and for inference concerning the coalescence time of the entire population.
Epigenome-wide association studies for common human diseases
This work discusses EWAS design, cohort and sample selections, statistical significance and power, confounding factors and follow-up studies, and how integration of EWASs with GWASs can help to dissect complex GWAS haplotypes for functional analysis.
Improved heritability estimation from genome-wide SNPs.
Population Structure and Cryptic Relatedness in Genetic Association Studies
This work views population structure and cryptic relatedness as different aspects of a single confounder: the unobserved pedigree defining the (often distant) relationships among the study subjects, and defines and estimates kinship coefficients, both pedigree-based and marker-based.
Simultaneous Analysis of All SNPs in Genome-Wide and Re-Sequencing Association Studies
This work shows that simultaneous analysis of the entire set of SNPs from a genome-wide study to identify the subset that best predicts disease outcome is now feasible, thanks to developments in stochastic search methods and derived an explicit approximation for type-I error that avoids the need to use permutation procedures.