ArticleGenetics2013
A Bayesian nonparametric approach for mapping dynamic quantitative traits.
Article in Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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Who cites it
18 citing papers in PubMed.
- Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records.Nature communications · 2024Article
- The Genetic Architecture of Juvenile Growth Traits in the ConiferFrontiers in plant science · 2022Article
- Pleiotropy and epistasis within and between signaling pathways defines the genetic architecture of fungal virulence.PLoS genetics · 2021Article
- Genetic control of tracheid properties in Norway spruce wood.Scientific reports · 2020Article
- Estimation of dynamic SNP-heritability with Bayesian Gaussian process models.Bioinformatics (Oxford, England) · 2020Article
- Integrating High-Throughput Phenotyping and Statistical Genomic Methods to Genetically Improve Longitudinal Traits in Crops.Frontiers in plant science · 2020Review
- Genome-wide association study identified novel candidate loci affecting wood formation in Norway spruce.The Plant journal : for cell and molecular biology · 2019Article
- A Gaussian process model and Bayesian variable selection for mapping function-valued quantitative traits with incomplete phenotypic data.Bioinformatics (Oxford, England) · 2019Article
- Functional Mapping of Quantitative Trait Loci (QTLs) Associated With Plant Performance in a Wheat MAGIC Mapping Population.Frontiers in plant science · 2018Article
- A Variational Bayes Genomic-Enabled Prediction Model with Genotype × Environment Interaction.G3 (Bethesda, Md.) · 2017Article
- Performance Gains in Genome-Wide Association Studies for Longitudinal Traits via Modeling Time-varied effects.Scientific reports · 2017Article
- Computational identification of genes modulating stem height-diameter allometry.Plant biotechnology journal · 2016Article
- A time-varying group sparse additive model for genome-wide association studies of dynamic complex traits.Bioinformatics (Oxford, England) · 2016Article
- Estimating Modifying Effect of Age on Genetic and Environmental Variance Components in Twin Models.Genetics · 2016Article
- A robust multiple-locus method for quantitative trait locus analysis of non-normally distributed multiple traits.Heredity · 2015Article
- Mapping Quantitative Trait Loci Underlying Function-Valued Traits Using Functional Principal Component Analysis and Multi-Trait Mapping.G3 (Bethesda, Md.) · 2015Article
- Dissecting dynamic genetic variation that controls temporal gene response in yeast.PLoS computational biology · 2014Article
- Functional multi-locus QTL mapping of temporal trends in Scots pine wood traits.G3 (Bethesda, Md.) · 2014Article
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In biology, many quantitative traits are dynamic in nature. They can often be described by some smooth functions or curves. A joint analysis of all the repeated measurements of the dynamic traits by functional quantitative trait loci (QTL) mapping methods has the benefits to (1) understand the genetic control of the whole dynamic process of the quantitative traits and (2) improve the statistical power to detect QTL. One crucial issue in functional QTL mapping is how to correctly describe the smoothness of trajectories of functional valued traits. We develop an efficient Bayesian nonparametric multiple-loci procedure for mapping dynamic traits. The method uses the Bayesian P-splines with (nonparametric) B-spline bases to specify the functional form of a QTL trajectory and a random walk prior to automatically determine its degree of smoothness. An efficient deterministic variational Bayes algorithm is used to implement both (1) the search of an optimal subset of QTL among large marker panels and (2) estimation of the genetic effects of the selected QTL changing over time. Our method can be fast even on some large-scale data sets. The advantages of our method are illustrated on both simulated and real data sets.
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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.