ArticleGenes2020
Combining Random Forests and a Signal Detection Method Leads to the Robust Detection of Genotype-Phenotype Associations.
Article in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.
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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.
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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
13 citing papers in PubMed, 19 citations in OpenAlex.
- Integrating multi-layer perceptron and random forest in an ensemble framework for improved genomic prediction accuracy and SHAP-derived interpretability of residual feed intake in cattle.Journal of animal science and biotechnology · 2026Article
- Random forest imputation and genomic prediction for missing egg production time-series data in yellow-feathered broiler breeders.BMC genomics · 2026Article
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- Computational Identification of Milk Trait Regulation Through Transcription Factor Cooperation in Murciano-Granadina Goats.Biology · 2024Article
- A divide-and-conquer approach for genomic prediction in rubber tree using machine learning.Scientific reports · 2022Article
- Novel Prehospital Phenotypes and Outcomes in Adult-Patients with Acute Disease.Journal of medical systems · 2022Article
- Deciphering Pleiotropic Signatures of Regulatory SNPs inInternational journal of molecular sciences · 2022Article
- Multi-Trait Multi-Environment Genomic Prediction for End-Use Quality Traits in Winter Wheat.Frontiers in genetics · 2022Article
- Expanding the conservation genomics toolbox: Incorporating structural variants to enhance genomic studies for species of conservation concern.Molecular ecology · 2021Article
- MIDESP: Mutual Information-Based Detection of Epistatic SNP Pairs for Qualitative and Quantitative Phenotypes.Biology · 2021Article
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- In Silico Identification of the Complex Interplay between Regulatory SNPs, Transcription Factors, and Their Related Genes inInternational journal of molecular sciences · 2021Article
- Article
Corrections and comments
- Erratum issued
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome wide association studies (GWAS) are a well established methodology to identify genomic variants and genes that are responsible for traits of interest in all branches of the life sciences. Despite the long time this methodology has had to mature the reliable detection of genotype-phenotype associations is still a challenge for many quantitative traits mainly because of the large number of genomic loci with weak individual effects on the trait under investigation. Thus, it can be hypothesized that many genomic variants that have a small, however real, effect remain unnoticed in many GWAS approaches. Here, we propose a two-step procedure to address this problem. In a first step, cubic splines are fitted to the test statistic values and genomic regions with spline-peaks that are higher than expected by chance are considered as quantitative trait loci (QTL). Then the SNPs in these QTLs are prioritized with respect to the strength of their association with the phenotype using a Random Forests approach. As a case study, we apply our procedure to real data sets and find trustworthy numbers of, partially novel, genomic variants and genes involved in various egg quality traits.
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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.