ArticleGenome biology2014
Effectively identifying regulatory hotspots while capturing expression heterogeneity in gene expression studies.
Article in Genome biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed.
- Identifying High-Dimensional Genomic Factors Modulating Biological Networks Across MultiOmics Data.bioRxiv : the preprint server for biology · 2025Article
- Phenotype integration improves power and preserves specificity in biobank-based genetic studies of major depressive disorder.Nature genetics · 2023Article
- Accurate modeling of replication rates in genome-wide association studies by accounting for Winner's Curse and study-specific heterogeneity.G3 (Bethesda, Md.) · 2022Article
- Fully automated web-based tool for identifying regulatory hotspots.BMC genomics · 2020Article
- GBAT: a gene-based association test for robust detection of trans-gene regulation.Genome biology · 2020Article
- Adjusting for Principal Components of Molecular Phenotypes Induces Replicating False Positives.Genetics · 2019Article
- Temporal genetic association and temporal genetic causality methods for dissecting complex networks.Nature communications · 2018Article
- Identification of putative regulatory regions and transcription factors associated with intramuscular fat content traits.BMC genomics · 2018Article
- An integrated -omics analysis of the epigenetic landscape of gene expression in human blood cells.BMC genomics · 2018Article
- Lead ModulatesFrontiers in genetics · 2018Article
- Applying meta-analysis to genotype-tissue expression data from multiple tissues to identify eQTLs and increase the number of eGenes.Bioinformatics (Oxford, England) · 2017Article
- An independent component analysis confounding factor correction framework for identifying broad impact expression quantitative trait loci.PLoS computational biology · 2017Article
- Integrated genome-wide analysis of expression quantitative trait loci aids interpretation of genomic association studies.Genome biology · 2017Article
- Regulatory Architecture of Gene Expression Variation in the Threespine Stickleback Gasterosteus aculeatus.G3 (Bethesda, Md.) · 2017Article
- Identification of Splicing Quantitative Trait Loci (sQTL) inFrontiers in genetics · 2017Article
- Efficient and Accurate Multiple-Phenotype Regression Method for High Dimensional Data Considering Population Structure.Genetics · 2016Article
- Computational discovery of transcription factors associated with drug response.The pharmacogenomics journal · 2016Article
- Article
- Multiple testing correction in linear mixed models.Genome biology · 2016Article
- Sparse regression models for unraveling group and individual associations in eQTL mapping.BMC bioinformatics · 2016Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Expression quantitative trait loci (eQTL) mapping is a tool that can systematically identify genetic variation affecting gene expression. eQTL mapping studies have shown that certain genomic locations, referred to as regulatory hotspots, may affect the expression levels of many genes. Recently, studies have shown that various confounding factors may induce spurious regulatory hotspots. Here, we introduce a novel statistical method that effectively eliminates spurious hotspots while retaining genuine hotspots. Applied to simulated and real datasets, we validate that our method achieves greater sensitivity while retaining low false discovery rates compared to previous methods.
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