Comparar métodos

	Análisis de series temporales de eQTL	Estudio de Asociación del Genoma Completo (GWAS)	Análisis de Mediación
Campo	Bioinformática	Bioinformática	Estadística
Familia	Process / pipeline	Process / pipeline	Hypothesis test
Año de origen	2010s–2019 (concept established earlier; dynamic framework formalized ~2019)	2005–2007	1986
Autor original	Multiple groups; formalized by Strober et al. and others in the context of cellular differentiation (2019)	Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007)	Baron & Kenny
Tipo	Genetic mapping method	Observational genomic association study	Indirect effects / path test
Fuente seminal	Fair, B. J., et al. (2020). Gene expression variability in human and chimpanzee populations share common determinants. eLife, 9, e59929.	Wellcome Trust Case Control Consortium. (2007). Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature, 447(7145), 661–678.	Baron, R. M. & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research. Journal of Personality and Social Psychology, 51(6), 1173–1182.
Alias	dynamic eQTL analysis, longitudinal eQTL mapping, ts-eQTL, temporal eQTL	GWAS, genome-wide association analysis, whole-genome association study, WGAS	indirect effects analysis, path-based mediation, PROCESS macro mediation, Aracılık Analizi (Mediation / PROCESS)
Relacionados	2	6	5
Resumen	Time-series eQTL analysis identifies genetic variants (eQTLs) whose effect on gene expression changes over time or across developmental stages. By combining longitudinal RNA-seq data with individual genotypes, the method captures how the same SNP can activate, silence, or reshape gene regulation at different time points — revealing the temporal architecture of the genome's regulatory program in processes such as differentiation, disease progression, and environmental response.	A genome-wide association study (GWAS) systematically tests hundreds of thousands to millions of single-nucleotide polymorphisms (SNPs) across the human genome for statistical association with a trait or disease. By comparing allele frequencies between cases and controls — or by regressing SNP genotypes on a quantitative phenotype — GWAS identifies genomic loci that harbor common genetic variants contributing to complex traits. Since its large-scale debut in 2007, GWAS has catalogued thousands of robust disease–variant associations across virtually every common human condition.	Mediation analysis is a statistical procedure that tests whether the effect of an independent variable X on an outcome Y operates wholly or partly through a third variable M, called the mediator. Formalised by Baron and Kenny in 1986, it decomposes the total effect of X on Y into a direct path (c′) and an indirect path (a × b), quantifying how much of the relationship is carried by the mediating mechanism.