Salīdzināt metodes

	Diferenciālā eQTL analīze	eQTL analīze
Nozare	Bioinformātika	Bioinformātika
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	2007–2012	2001 (term coined); widely adopted after 2005
Autors	Pioneered by GTEx Consortium and Stranger et al.; formal differential testing approaches developed ~2007–2012	Ritsert C. Jansen & Jan-Peter Nap
Tips	Statistical genomics pipeline	Association mapping method
Pirmavots	Stranger, B. E., et al. (2007). Relative impact of nucleotide and copy number variation on gene expression phenotypes. Science, 315(5813), 848–853.	Jansen, R. C., & Nap, J.-P. (2001). Genetical genomics: the added value from segregation. Trends in Genetics, 17(7), 388–391.
Citi nosaukumi	deQTL analysis, context-specific eQTL, interaction eQTL, conditional eQTL	eQTL mapping, expression QTL analysis, transcriptomic QTL analysis, eQTL study
Saistītās	6	6
Kopsavilkums	Differential eQTL analysis identifies genetic variants — expression quantitative trait loci — whose regulatory effect on gene expression varies systematically across biological conditions such as tissue types, disease states, developmental stages, or treatment groups. By testing for statistical interactions between genotype and condition, the method pinpoints loci where the same allele has different transcriptional consequences depending on context, revealing the molecular basis of condition-specific gene regulation.	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.