ArticleGenetics2013
A novel generalized ridge regression method for quantitative genetics.
Article in Genetics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.
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Who cites it
41 citing papers in PubMed.
- Haplotype-based autoencoders can reduce the dataset dimension and estimate haplotype block effects in different crop species.BMC bioinformatics · 2025Article
- Hierarchical selection of genetic and gene by environment interaction effects in high-dimensional mixed models.Statistical methods in medical research · 2025Review
- Transcriptional profiles reveal histologic origin and prognosis across 33 The Cancer Genome Atlas tumor types.Translational cancer research · 2023Article
- Genomic prediction with haplotype blocks in wheat.Frontiers in plant science · 2023Article
- G2P Provides an Integrative Environment for Multi-model genomic selection analysis to improve genotype-to-phenotype prediction.Frontiers in plant science · 2023Article
- Estimating genetic variance contributed by a quantitative trait locus: A random model approach.PLoS computational biology · 2022Article
- Plant Genotype to Phenotype Prediction Using Machine Learning.Frontiers in genetics · 2022Review
- NeuralLasso: Neural Networks Meet Lasso in Genomic Prediction.Frontiers in plant science · 2022Article
- Identification of SNPs Associated with Somatic Cell Score in Candidate Genes in Italian Holstein Friesian Bulls.Animals : an open access journal from MDPI · 2021Article
- PATRIOT: A Pipeline for Tracing Identity-by-Descent for Chromosome Segments to Improve Genomic Prediction in Self-Pollinating Crop Species.Frontiers in plant science · 2021Article
- Genome-wide association studies using binned genotypes.Heredity · 2020Article
- Genomic Prediction Including SNP-Specific Variance Predictors.G3 (Bethesda, Md.) · 2019Article
- Interactions of Tomato andThe Plant cell · 2019Article
- Digital Imaging Combined with Genome-Wide Association Mapping Links Loci to Plant-Pathogen Interaction Traits.Plant physiology · 2018Article
- A linear mixed model framework for gene-based gene-environment interaction tests in twin studies.Genetic epidemiology · 2018Article
- A rapid epistatic mixed-model association analysis by linear retransformations of genomic estimated values.Bioinformatics (Oxford, England) · 2018Article
- A novel linkage-disequilibrium corrected genomic relationship matrix for SNP-heritability estimation and genomic prediction.Heredity · 2018Article
- Genomic prediction accuracies in space and time for height and wood density of Douglas-fir using exome capture as the genotyping platform.BMC genomics · 2017Article
- An Efficient Test for Gene-Environment Interaction in Generalized Linear Mixed Models with Family Data.International journal of environmental research and public health · 2017Article
- Network-Guided GWAS Improves Identification of Genes Affecting Free Amino Acids.Plant physiology · 2017Article
Corrections and comments
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4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As the molecular marker density grows, there is a strong need in both genome-wide association studies and genomic selection to fit models with a large number of parameters. Here we present a computationally efficient generalized ridge regression (RR) algorithm for situations in which the number of parameters largely exceeds the number of observations. The computationally demanding parts of the method depend mainly on the number of observations and not the number of parameters. The algorithm was implemented in the R package bigRR based on the previously developed package hglm. Using such an approach, a heteroscedastic effects model (HEM) was also developed, implemented, and tested. The efficiency for different data sizes were evaluated via simulation. The method was tested for a bacteria-hypersensitive trait in a publicly available Arabidopsis data set including 84 inbred lines and 216,130 SNPs. The computation of all the SNP effects required <10 sec using a single 2.7-GHz core. The advantage in run time makes permutation test feasible for such a whole-genome model, so that a genome-wide significance threshold can be obtained. HEM was found to be more robust than ordinary RR (a.k.a. SNP-best linear unbiased prediction) in terms of QTL mapping, because SNP-specific shrinkage was applied instead of a common shrinkage. The proposed algorithm was also assessed for genomic evaluation and was shown to give better predictions than ordinary RR.
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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.