ArticleBMC bioinformatics2006
PSMIX: an R package for population structure inference via maximum likelihood method.
Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed.
- Dual-specificity phosphatase 1 as a pharmacogenetic modifier of inhaled steroid response among asthmatic patients.The Journal of allergy and clinical immunology · 2010Trial
- Insights from Population Genomics to Enhance and Sustain Biological Control of Insect Pests.Insects · 2020Review
- Nonparametric approaches for population structure analysis.Human genomics · 2018Review
- Assessment of Genetic Heterogeneity in Structured Plant Populations Using Multivariate Whole-Genome Regression Models.Genetics · 2015Article
- A fast least-squares algorithm for population inference.BMC bioinformatics · 2013Article
- Comparison of measures of marker informativeness for ancestry and admixture mapping.BMC genomics · 2011Article
- Article
- Characterization of a Bayesian genetic clustering algorithm based on a Dirichlet process prior and comparison among Bayesian clustering methods.BMC bioinformatics · 2011Article
- Controlling Population Structure in Human Genetic Association Studies with Samples of Unrelated Individuals.Statistics and its interface · 2011Article
- Factors predicting inhaled corticosteroid responsiveness in African American patients with asthma.The Journal of allergy and clinical immunology · 2010Article
- Mapping genes that predict treatment outcome in admixed populations.The pharmacogenomics journal · 2010Article
- Genetic ancestry in lung-function predictions.The New England journal of medicine · 2010Article
- Iterative pruning PCA improves resolution of highly structured populations.BMC bioinformatics · 2009Article
- Assessing population genetic structure via the maximisation of genetic distance.Genetics, selection, evolution : GSE · 2009Article
- The use of plasmodes as a supplement to simulations: A simple example evaluating individual admixture estimation methodologies.Computational statistics & data analysis · 2009Article
- Evaluating the impact of scoring parameters on the structure of intra-specific genetic variation using RawGeno, an R package for automating AFLP scoring.BMC bioinformatics · 2009Article
- Comparison of statistical methods for estimating genetic admixture in a lung cancer study of African Americans and Latinos.American journal of epidemiology · 2008Article
- Differences in allergic sensitization by self-reported race and genetic ancestry.The Journal of allergy and clinical immunology · 2008Article
- AWclust: point-and-click software for non-parametric population structure analysis.BMC bioinformatics · 2008Article
- Review and evaluation of methods correcting for population stratification with a focus on underlying statistical principles.Human heredity · 2008Review
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
backgroundInference of population stratification and individual admixture from genetic markers is an integrative part of a study in diverse situations, such as association mapping and evolutionary studies. Bayesian methods have been proposed for population stratification and admixture inference using multilocus genotypes and widely used in practice. However, these Bayesian methods demand intensive computation resources and may run into convergence problem in Markov Chain Monte Carlo based posterior samplings.
resultsWe have developed PSMIX, an R package based on maximum likelihood method using expectation-maximization algorithm, for inference of population stratification and individual admixture.
conclusionCompared with software based on Bayesian methods (e.g., STRUCTURE), PSMIX has similar accuracy, but more efficient computations.PSMIX and its supplemental documents are freely available at http://bioinformatics.med.yale.edu/PSMIX.
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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.