Bandingkan metode

	Analisis eQTL Multi-Omik	Analisis eQTL
Bidang	Bioinformatika	Bioinformatika
Keluarga	Process / pipeline	Process / pipeline
Tahun asal	2010s–present (foundational eQTL work: ~2007; multi-omics integration: ~2013–2017)	2001 (term coined); widely adopted after 2005
Pencetus	GTEx Consortium and multi-omics integration pioneers (Nica & Dermitzakis, 2013; GTEx Consortium, 2015–2020)	Ritsert C. Jansen & Jan-Peter Nap
Tipe	Integrative genomic association analysis	Association mapping method
Sumber perintis	GTEx Consortium. (2017). Genetic effects on gene expression across human tissues. Nature, 550(7675), 204–213.	Jansen, R. C., & Nap, J.-P. (2001). Genetical genomics: the added value from segregation. Trends in Genetics, 17(7), 388–391.
Alias	multi-omics molQTL, multi-layer eQTL, integrated eQTL analysis, xQTL multi-omics	eQTL mapping, expression QTL analysis, transcriptomic QTL analysis, eQTL study
Terkait	6	6
Ringkasan	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.	eQTL analysis identifies genomic loci (variants, typically SNPs) whose genotype statistically associates with variation in the expression level of one or more genes. By jointly profiling DNA-level variation and RNA-level expression in the same individuals, eQTL studies decode the regulatory grammar of the genome — revealing which variants control how much a gene is transcribed, in which tissues, and under what conditions.