ArticleBioinformatics (Oxford, England)2019
Integration of methylation QTL and enhancer-target gene maps with schizophrenia GWAS summary results identifies novel genes.
Article in Bioinformatics (Oxford, England), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Identification of key candidate genes regulating hundred-grain weight in the maize inbred line Ye107 from Southern China.Plant cell reports · 2025Article
- Methylome-wide and meQTL analysis helps to distinguish treatment response from non-response and pathogenesis markers in schizophrenia.Frontiers in psychiatry · 2024Article
- Evaluating 17 methods incorporating biological function with GWAS summary statistics to accelerate discovery demonstrates a tradeoff between high sensitivity and high positive predictive value.Communications biology · 2023Article
- Dissecting the shared genetic basis of migraine and mental disorders using novel statistical tools.Brain : a journal of neurology · 2022Article
- Identification of genetic variants influencing methylation in brain with pleiotropic effects on psychiatric disorders.Progress in neuro-psychopharmacology & biological psychiatry · 2022Article
- Understanding the function of regulatory DNA interactions in the interpretation of non-coding GWAS variants.Frontiers in cell and developmental biology · 2022Review
- Using expression quantitative trait loci data and graph-embedded neural networks to uncover genotype-phenotype interactions.Frontiers in genetics · 2022Article
- An integrative multiomics analysis identifies putative causal genes for COVID-19 severity.Genetics in medicine : official journal of the American College of Medical Genetics · 2021Article
- A gene-level methylome-wide association analysis identifies novel Alzheimer's disease genes.Bioinformatics (Oxford, England) · 2021Article
- Linking genotype to phenotype in multi-omics data of small sample.BMC genomics · 2021Article
- Leveraging existing GWAS summary data of genetically correlated and uncorrelated traits to improve power for a new GWAS.Genetic epidemiology · 2020Article
- Integrating DNA sequencing and transcriptomic data for association analyses of low-frequency variants and lipid traits.Human molecular genetics · 2020Article
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2 authors.
Funding
Abstract
motivationMost trait-associated genetic variants identified in genome-wide association studies (GWASs) are located in non-coding regions of the genome and thought to act through their regulatory roles.
resultsTo account for enriched association signals in DNA regulatory elements, we propose a novel and general gene-based association testing strategy that integrates enhancer-target gene pairs and methylation quantitative trait locus data with GWAS summary results; it aims to both boost statistical power for new discoveries and enhance mechanistic interpretability of any new discovery. By reanalyzing two large-scale schizophrenia GWAS summary datasets, we demonstrate that the proposed method could identify some significant and novel genes (containing no genome-wide significant SNPs nearby) that would have been missed by other competing approaches, including the standard and some integrative gene-based association methods, such as one incorporating enhancer-target gene pairs and one integrating expression quantitative trait loci. AVAILABILITY AND IMPLEMENTATION: Software: wuchong.org/egmethyl.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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