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기계 학습 보조 eQTL 분석×Multi-omics eQTL Analysis×
분야생물정보학생물정보학
계열Process / pipelineProcess / pipeline
기원 연도2015 (key ML-eQTL methods; foundational eQTL work: Jansen & Nap 2001)2010s–present (foundational eQTL work: ~2007; multi-omics integration: ~2013–2017)
창시자Gamazon et al. (PrediXcan), Zhou & Troyanskaya (DeepSEA); broader field ca. 2015-onwardGTEx Consortium and multi-omics integration pioneers (Nica & Dermitzakis, 2013; GTEx Consortium, 2015–2020)
유형Statistical-computational genomics pipelineIntegrative genomic association analysis
원전Gamazon, E. R., Wheeler, H. E., Shah, K. P., Mozaffari, S. V., Aquino-Michaels, K., Carroll, R. J., ... & Im, H. K. (2015). A gene-based association method for mapping traits using reference transcriptome data. Nature Genetics, 47(9), 1091-1098. link ↗GTEx Consortium. (2017). Genetic effects on gene expression across human tissues. Nature, 550(7675), 204–213. link ↗
별칭ML-assisted eQTL analysis, ML eQTL mapping, deep learning eQTL, predictive eQTL modelingmulti-omics molQTL, multi-layer eQTL, integrated eQTL analysis, xQTL multi-omics
관련66
요약Machine learning-assisted eQTL analysis integrates supervised learning models — ranging from elastic-net regression to deep neural networks — into the classical eQTL framework to predict and map genetic variants that regulate gene expression. By training predictive models on reference panels (e.g., GTEx), the approach enables imputation of gene expression in cohorts lacking RNA data, substantially increasing statistical power and enabling trans-tissue generalisation.Multi-omics eQTL analysis maps genetic variants (SNPs or structural variants) to molecular phenotypes simultaneously across multiple omics layers — transcriptome, epigenome, proteome, and metabolome — in the same cohort. By linking genotype to gene expression and then tracing those effects through downstream molecular layers, the approach reveals how genetic variation propagates through the molecular machinery of a cell, yielding mechanistic insight that no single-omics eQTL study can provide.
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ScholarGate방법 비교: Machine learning-assisted expression quantitative trait loci analysis · Multi-omics eQTL analysis. 2026-06-15에 다음에서 검색함: https://scholargate.app/ko/compare