Comparer des méthodes

	Analyse bayésienne des eQTL	Analyse des QTL d'expression
Domaine	Bio-informatique	Bio-informatique
Famille	Process / pipeline	Process / pipeline
Année d'origine	2000s–2010s	2001 (term coined); widely adopted after 2005
Auteur d'origine	Matthew Stephens, David J. Balding (Bayesian framework for genetic association); extended by multiple groups for eQTL context	Ritsert C. Jansen & Jan-Peter Nap
Type	Probabilistic genomic association method	Association mapping method
Source fondatrice	Stephens, M., & Balding, D. J. (2009). Bayesian statistical methods for genetic association studies. Nature Reviews Genetics, 10(10), 681–690.	Jansen, R. C., & Nap, J.-P. (2001). Genetical genomics: the added value from segregation. Trends in Genetics, 17(7), 388–391.
Alias	Bayesian eQTL mapping, probabilistic eQTL analysis, Bayesian QTL mapping for gene expression, eQTL fine-mapping	eQTL mapping, expression QTL analysis, transcriptomic QTL analysis, eQTL study
Apparentées	6	6
Résumé	Bayesian eQTL analysis identifies genetic variants (eQTLs) that regulate gene expression by combining genotype and RNA-seq data within a probabilistic framework. Unlike frequentist approaches that rely on p-value thresholds, the Bayesian formulation produces posterior probabilities of association, enabling principled fine-mapping of causal variants and coherent uncertainty quantification across thousands of gene-SNP pairs simultaneously.	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.