ReviewTrends in genetics : TIG2018
Complex-Trait Prediction in the Era of Big Data.
Review in Trends in genetics : TIG, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 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
34 citing papers in PubMed.
- Hiding in plain sight: uncovering the genetic basis of complex phenotypes through low-risk groups.Genetics · 2026Article
- Predictive models of the genetic bases underlying budding yeast fitness in multiple environments.NAR genomics and bioinformatics · 2026Article
- Highly Polygenic Control of Photosynthetic Responses to Nighttime Temperature Studied by Genomic Prediction.Plant, cell & environment · 2026Article
- Improving polygenic score prediction for underrepresented groups through transfer learning.Nature communications · 2026Article
- Statistical construction of calibrated prediction intervals for polygenic score-based phenotype prediction.Nature genetics · 2025Article
- Predicting Forest Tree Leaf Phenology Under Climate Change Using Satellite Monitoring and Population-Based Genomic Trait Association.Global change biology · 2025Article
- Bridging Genomics to Cardiology Clinical Practice: Artificial Intelligence in Optimizing Polygenic Risk Scores: A Systematic Review.JACC. Advances · 2025Review
- TraitTrainR: accelerating large-scale simulation under models of continuous trait evolution.Bioinformatics advances · 2025Article
- Bayesian hierarchical hypothesis testing in large-scale genome-wide association analysis.Genetics · 2024Article
- Patterns of information literacy and their predictors among emergency department nurses: a latent profile analysis based on the person-context interaction theory.BMC nursing · 2024Article
- Exploring the potential of incremental feature selection to improve genomic prediction accuracy.Genetics, selection, evolution : GSE · 2023Article
- mtPGS: Leverage multiple correlated traits for accurate polygenic score construction.American journal of human genetics · 2023Article
- Predictive modeling of antibiotic eradication therapy success for new-onset Pseudomonas aeruginosa pulmonary infections in children with cystic fibrosis.PLoS computational biology · 2023Article
- LLM-PBC: Logic Learning Machine-Based Explainable Rules Accurately Stratify the Genetic Risk of Primary Biliary Cholangitis.Journal of personalized medicine · 2022Article
- Review
- Searching for improvements in predicting human eye colour from DNA.International journal of legal medicine · 2021Article
- Genetic drift from the out-of-Africa bottleneck leads to biased estimation of genetic architecture and selection.European journal of human genetics : EJHG · 2021Article
- Genetic correlations between traits associated with hyperuricemia, gout, and comorbidities.European journal of human genetics : EJHG · 2021Article
- Machine Learning Prediction of Biomarkers from SNPs and of Disease Risk from Biomarkers in the UK Biobank.Genes · 2021Article
- Robust modeling of additive and nonadditive variation with intuitive inclusion of expert knowledge.Genetics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
Accurate prediction of complex traits requires using a large number of DNA variants. Advances in statistical and machine learning methodology enable the identification of complex patterns in high-dimensional settings. However, training these highly parameterized methods requires very large data sets. Until recently, such data sets were not available. But the situation is changing rapidly as very large biomedical data sets comprising individual genotype-phenotype data for hundreds of thousands of individuals become available in public and private domains. We argue that the convergence of advances in methodology and the advent of Big Genomic Data will enable unprecedented improvements in complex-trait prediction; we review theory and evidence supporting our claim and discuss challenges and opportunities that Big Data will bring to complex-trait prediction.
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What OpenQuestion holds
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.