ArticleGenetics2009
Hierarchical generalized linear models for multiple quantitative trait locus mapping.
Article in Genetics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
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Who cites it
45 citing papers in PubMed.
- Functional principal component models for sparse and irregularly spaced data by Bayesian inference.Journal of applied statistics · 2024Article
- FMixFN: A Fast Big Data-Oriented Genomic Selection Model Based on an Iterative Conditional Expectation algorithm.Frontiers in genetics · 2021Article
- MaximumG3 (Bethesda, Md.) · 2020Article
- A Multi-Locus Association Model Framework for Nested Association Mapping With Discriminating QTL Effects in Various Subpopulations.Frontiers in genetics · 2020Article
- BhGLM: Bayesian hierarchical GLMs and survival models, with applications to genomics and epidemiology.Bioinformatics (Oxford, England) · 2019Article
- A fast algorithm for Bayesian multi-locus model in genome-wide association studies.Molecular genetics and genomics : MGG · 2017Article
- Genetic dissection of heterosis using epistatic association mapping in a partial NCII mating design.Scientific reports · 2015Article
- Bayesian variable selection for hierarchical gene-environment and gene-gene interactions.Human genetics · 2015Article
- Interacted QTL mapping in partial NCII design provides evidences for breeding by design.PloS one · 2015Article
- Mapping epistatic quantitative trait loci.BMC genetics · 2014Article
- Multiple comparisons in genetic association studies: a hierarchical modeling approach.Statistical applications in genetics and molecular biology · 2014Article
- Generalized linear model for mapping discrete trait loci implemented with LASSO algorithm.PloS one · 2014Article
- Whole-genome quantitative trait locus mapping reveals major role of epistasis on yield of rice.PloS one · 2014Article
- Fast genomic predictions via Bayesian G-BLUP and multilocus models of threshold traits including censored Gaussian data.G3 (Bethesda, Md.) · 2013Article
- Clinical and genetic predictors of weight gain in patients diagnosed with breast cancer.British journal of cancer · 2013Article
- Article
- Bayesian Methods for High Dimensional Linear Models.Journal of biometrics & biostatistics · 2013Article
- Empirical Bayesian LASSO-logistic regression for multiple binary trait locus mapping.BMC genetics · 2013Article
- Review
- A Bayesian method and its variational approximation for prediction of genomic breeding values in multiple traits.BMC bioinformatics · 2013Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
We develop hierarchical generalized linear models and computationally efficient algorithms for genomewide analysis of quantitative trait loci (QTL) for various types of phenotypes in experimental crosses. The proposed models can fit a large number of effects, including covariates, main effects of numerous loci, and gene-gene (epistasis) and gene-environment (G x E) interactions. The key to the approach is the use of continuous prior distribution on coefficients that favors sparseness in the fitted model and facilitates computation. We develop a fast expectation-maximization (EM) algorithm to fit models by estimating posterior modes of coefficients. We incorporate our algorithm into the iteratively weighted least squares for classical generalized linear models as implemented in the package R. We propose a model search strategy to build a parsimonious model. Our method takes advantage of the special correlation structure in QTL data. Simulation studies demonstrate reasonable power to detect true effects, while controlling the rate of false positives. We illustrate with three real data sets and compare our method to existing methods for multiple-QTL mapping. Our method has been implemented in our freely available package R/qtlbim (www.qtlbim.org), providing a valuable addition to our previous Markov chain Monte Carlo (MCMC) approach.
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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.