Compară metode

	Analiza eQTL bazată pe rețele	Analiza eQTL
Domeniu	Bioinformatică	Bioinformatică
Familie	Process / pipeline	Process / pipeline
Anul apariției	2008–2013 (network-integrated extensions of eQTL mapping)	2001 (term coined); widely adopted after 2005
Autorul original	Multiple groups; foundational eQTL work by Cheung et al. (2005) and Stranger et al. (2007); network integration extended by Zhu et al. (2008) and others	Ritsert C. Jansen & Jan-Peter Nap
Tip	Statistical genomics / network analysis pipeline	Association mapping method
Sursa seminală	Skinner, M. E., Uzilov, A. V., Stein, L. D., Mungall, C. J., & Holmes, I. H. (2009). JBrowse: a next-generation genome browser. Genome Research, 19(9), 1630–1638.	Jansen, R. C., & Nap, J.-P. (2001). Genetical genomics: the added value from segregation. Trends in Genetics, 17(7), 388–391.
Denumiri alternative	network eQTL, network-integrated eQTL mapping, graph-based eQTL analysis, eQTL network analysis	eQTL mapping, expression QTL analysis, transcriptomic QTL analysis, eQTL study
Înrudite	5	6
Rezumat	Network-based eQTL analysis extends classical eQTL mapping by embedding genetic variant-to-expression associations within gene regulatory or protein interaction networks. Rather than treating each SNP-gene pair independently, this approach leverages network topology — such as co-expression modules or known pathway structures — to improve statistical power, reduce multiple testing burden, and reveal how genetic variants perturb entire regulatory programs rather than isolated transcripts.	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.