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	Multi-omics eQTL Analysis	आरएनए-सीक्वेंसिंग विभेदक अभिव्यक्ति
क्षेत्र	जैव सूचना विज्ञान	जैव सूचना विज्ञान
परिवार	Process / pipeline	Process / pipeline
उद्भव वर्ष	2010s–present (foundational eQTL work: ~2007; multi-omics integration: ~2013–2017)	2008–2010 (RNA-seq DE methodology established)
प्रवर्तक	GTEx Consortium and multi-omics integration pioneers (Nica & Dermitzakis, 2013; GTEx Consortium, 2015–2020)	Multiple groups; foundational methods from Anders & Huber (DESeq, 2010), Robinson, McCarthy & Smyth (edgeR, 2010)
प्रकार	Integrative genomic association analysis	Quantitative genomics pipeline
मौलिक स्रोत	GTEx Consortium. (2017). Genetic effects on gene expression across human tissues. Nature, 550(7675), 204–213.	Love, M. I., Huber, W., & Anders, S. (2014). Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology, 15(12), 550.
उपनाम	multi-omics molQTL, multi-layer eQTL, integrated eQTL analysis, xQTL multi-omics	RNA-seq DE analysis, transcriptomic differential expression, bulk RNA-seq DE, DEA
संबंधित	6	6
सारांश	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.	RNA-seq differential expression (DE) analysis identifies genes whose transcript abundance differs significantly between two or more biological conditions — for example, treated versus control, or diseased versus healthy tissue. Starting from raw sequencing reads, the pipeline moves through alignment, count-based normalization, statistical modeling of count dispersion, hypothesis testing, and multiple-testing correction to produce a ranked list of differentially expressed genes accompanied by fold-change estimates and adjusted p-values.