ArticleHuman genetics2011
A dynamic model for genome-wide association studies.
Article in Human genetics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 47 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
47 citing papers in PubMed.
- FEMA-Long: Modeling unstructured covariances for discovery of time-dependent effects in large-scale longitudinal datasets.PLoS genetics · 2026Article
- A Statistical Mechanics Model to Decode Tissue Crosstalk During Graft Formation.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Longitudinal Genome-Wide Association Study for Female Fertility Traits in German Holstein Cattle.Animal genetics · 2026Article
- Identifying New Loci and Genes Associated with Feed Efficiency in Broilers.International journal of molecular sciences · 2025Article
- Exploiting light energy utilization strategies in Populus simonii through multitrait-GWAS: insights from stochastic differential models.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2024Article
- Characterising the genetic architecture of changes in adiposity during adulthood using electronic health records.Nature communications · 2024Article
- RETROSPECTIVE VARYING COEFFICIENT ASSOCIATION ANALYSIS OF LONGITUDINAL BINARY TRAITS: APPLICATION TO THE IDENTIFICATION OF GENETIC LOCI ASSOCIATED WITH HYPERTENSION.The annals of applied statistics · 2024Article
- A Bayesian random regression method using mixture priors for genome-enabled analysis of time-series high-throughput phenotyping data.The plant genome · 2022Article
- Statistical Methods for the Quantitative Genetic Analysis of High-Throughput Phenotyping Data.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Gene Region Association Analysis of Longitudinal Quantitative Traits Based on a Function-On-Function Regression Model.Frontiers in genetics · 2022Article
- Genomic Prediction of Green Fraction Dynamics in Soybean Using Unmanned Aerial Vehicles Observations.Frontiers in plant science · 2022Article
- Inferring multilayer interactome networks shaping phenotypic plasticity and evolution.Nature communications · 2021Article
- Genome-Wide Association Study Based on Random Regression Model Reveals Candidate Genes Associated with Longitudinal Data in Chinese Simmental Beef Cattle.Animals : an open access journal from MDPI · 2021Article
- Interaction analyses based on growth parameters of GWAS between Escherichia coli and Staphylococcus aureus.AMB Express · 2021Article
- Genome-Wide Association Analysis of Growth Curve Parameters in Chinese Simmental Beef Cattle.Animals : an open access journal from MDPI · 2021Article
- Genetic dissection of growth trajectories in forest trees: From FunMap to FunGraph.Forestry research · 2021Review
- Leveraging genome-enabled growth models to study shoot growth responses to water deficit in rice.Journal of experimental botany · 2020Article
- Multiple association analysis of loci and candidate genes that regulate body size at three growth stages in Simmental beef cattle.BMC genetics · 2020Article
- Integrating High-Throughput Phenotyping and Statistical Genomic Methods to Genetically Improve Longitudinal Traits in Crops.Frontiers in plant science · 2020Review
- Retrospective Association Analysis of Longitudinal Binary Traits Identifies Important Loci and Pathways in Cocaine Use.Genetics · 2019Article
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
Abstract
Although genome-wide association studies (GWAS) are widely used to identify the genetic and environmental etiology of a trait, several key issues related to their statistical power and biological relevance have remained unexplored. Here, we describe a novel statistical approach, called functional GWAS or fGWAS, to analyze the genetic control of traits by integrating biological principles of trait formation into the GWAS framework through mathematical and statistical bridges. fGWAS can address many fundamental questions, such as the patterns of genetic control over development, the duration of genetic effects, as well as what causes developmental trajectories to change or stop changing. In statistics, fGWAS displays increased power for gene detection by capitalizing on cumulative phenotypic variation in a longitudinal trait over time and increased robustness for manipulating sparse longitudinal data.
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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.