SynthesisAnimal genetics2016
Meta-analysis of genome-wide association from genomic prediction models.
Synthesis in Animal genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
20 citing papers in PubMed.
- Article
- Integrative Machine Learning Approaches for Identifying Loci Associated with Anthracnose Resistance in Strawberry.Plants (Basel, Switzerland) · 2025Article
- Comparison of genomic prediction accuracy using different models for egg production traits in Taiwan country chicken.Poultry science · 2024Article
- Marker effect p-values for single-step GWAS with the algorithm for proven and young in large genotyped populations.Genetics, selection, evolution : GSE · 2024Article
- Genomic Prediction and Genome-Wide Association Study for Boar Taint Compounds.Animals : an open access journal from MDPI · 2023Article
- Genomic selection and genome-wide association studies in tetraploid chipping potatoes.The plant genome · 2023Article
- Microbiability and microbiome-wide association analyses of feed efficiency and performance traits in pigs.Genetics, selection, evolution : GSE · 2022Article
- Non-additive QTL mapping of lactation traits in 124,000 cattle reveals novel recessive loci.Genetics, selection, evolution : GSE · 2022Article
- Non-additive association analysis using proxy phenotypes identifies novel cattle syndromes.Nature genetics · 2021Article
- Emerging issues in genomic selection.Journal of animal science · 2021Article
- Accounting for Population Structure and Phenotypes From Relatives in Association Mapping for Farm Animals: A Simulation Study.Frontiers in genetics · 2021Article
- Inbreeding depression across the genome of Dutch Holstein Friesian dairy cattle.Genetics, selection, evolution : GSE · 2020Article
- Genetic control of tracheid properties in Norway spruce wood.Scientific reports · 2020Article
- Single-Step Genomic Evaluations from Theory to Practice: Using SNP Chips and Sequence Data in BLUPF90.Genes · 2020Review
- Estimation of dynamic SNP-heritability with Bayesian Gaussian process models.Bioinformatics (Oxford, England) · 2020Article
- Current status of genomic evaluation.Journal of animal science · 2020Review
- Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle.Genetics, selection, evolution : GSE · 2019Article
- GWAS by GBLUP: Single and Multimarker EMMAX and Bayes Factors, with an Example in Detection of a Major Gene for Horse Gait.G3 (Bethesda, Md.) · 2018Article
- Article
- Integrative Analysis of Metabolomic, Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs.International journal of molecular sciences · 2016Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association (GWA) studies based on GBLUP models are a common practice in animal breeding. However, effect sizes of GWA tests are small, requiring larger sample sizes to enhance power of detection of rare variants. Because of difficulties in increasing sample size in animal populations, one alternative is to implement a meta-analysis (MA), combining information and results from independent GWA studies. Although this methodology has been used widely in human genetics, implementation in animal breeding has been limited. Thus, we present methods to implement a MA of GWA, describing the proper approach to compute weights derived from multiple genomic evaluations based on animal-centric GBLUP models. Application to real datasets shows that MA increases power of detection of associations in comparison with population-level GWA, allowing for population structure and heterogeneity of variance components across populations to be accounted for. Another advantage of MA is that it does not require access to genotype data that is required for a joint analysis. Scripts related to the implementation of this approach, which consider the strength of association as well as the sign, are distributed and thus account for heterogeneity in association phase between QTL and SNPs. Thus, MA of GWA is an attractive alternative to summarizing results from multiple genomic studies, avoiding restrictions with genotype data sharing, definition of fixed effects and different scales of measurement of evaluated traits.
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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 Socratic graph.