ArticleHeredity2015
Empirical Bayesian elastic net for multiple quantitative trait locus mapping.
Article in Heredity, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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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Who cites it
11 citing papers in PubMed, 30 citations in OpenAlex.
- Development of Plasma Protein Classification Models for Alzheimer's Disease Using Multiple Machine Learning Approaches.International journal of molecular sciences · 2025Article
- FSF-GA: A Feature Selection Framework for Phenotype Prediction Using Genetic Algorithms.Genes · 2023Article
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- Pharmacogene Variants Associated with Liver Transplant in a Twelve-Year Clinical Follow-Up.Pharmaceutics · 2022Article
- A parallelized strategy for epistasis analysis based on Empirical Bayesian Elastic Net models.Bioinformatics (Oxford, England) · 2020Article
- Article
- Identifying the Driving Factors of Black Bloom in Lake Bay through Bayesian LASSO.International journal of environmental research and public health · 2019Article
- MVQTLCIM: composite interval mapping of multivariate traits in a hybrid FBMC bioinformatics · 2017Article
- Epistasis analysis of microRNAs on pathological stages in colon cancer based on an Empirical Bayesian Elastic Net method.BMC genomics · 2017Article
- Genetic dissection of heterosis using epistatic association mapping in a partial NCII mating design.Scientific reports · 2015Article
- Interacted QTL mapping in partial NCII design provides evidences for breeding by design.PloS one · 2015Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In multiple quantitative trait locus (QTL) mapping, a high-dimensional sparse regression model is usually employed to account for possible multiple linked QTLs. The QTL model may include closely linked and thus highly correlated genetic markers, especially when high-density marker maps are used in QTL mapping because of the advancement in sequencing technology. Although existing algorithms, such as Lasso, empirical Bayesian Lasso (EBlasso) and elastic net (EN) are available to infer such QTL models, more powerful methods are highly desirable to detect more QTLs in the presence of correlated QTLs. We developed a novel empirical Bayesian EN (EBEN) algorithm for multiple QTL mapping that inherits the efficiency of our previously developed EBlasso algorithm. Simulation results demonstrated that EBEN provided higher power of detection and almost the same false discovery rate compared with EN and EBlasso. Particularly, EBEN can identify correlated QTLs that the other two algorithms may fail to identify. When analyzing a real dataset, EBEN detected more effects than EN and EBlasso. EBEN provides a useful tool for inferring high-dimensional sparse model in multiple QTL mapping and other applications. An R software package 'EBEN' implementing the EBEN algorithm is available on the Comprehensive R Archive Network (CRAN).
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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.