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| 베이즈 경로 농축 분석× | eQTL 분석× | |
|---|---|---|
| 분야 | 생물정보학 | 생물정보학 |
| 계열 | Process / pipeline | Process / pipeline |
| 기원 연도≠ | 2001–2007 | 2001 (term coined); widely adopted after 2005 |
| 창시자≠ | Pierre Baldi, Anthony Long; Michael Newton et al. (foundational Bayesian gene-set frameworks) | Ritsert C. Jansen & Jan-Peter Nap |
| 유형≠ | Probabilistic gene-set testing | Association mapping method |
| 원전≠ | Baldi, P., & Long, A. D. (2001). A Bayesian framework for the analysis of microarray expression data: regularized t-test and statistical inferences of gene changes. Bioinformatics, 17(6), 509–519. DOI ↗ | Jansen, R. C., & Nap, J.-P. (2001). Genetical genomics: the added value from segregation. Trends in Genetics, 17(7), 388–391. DOI ↗ |
| 별칭 | Bayesian gene-set testing, Bayesian GSEA, Bayesian functional enrichment, BGSEA | eQTL mapping, expression QTL analysis, transcriptomic QTL analysis, eQTL study |
| 관련 | 6 | 6 |
| 요약≠ | Bayesian pathway enrichment analysis tests whether a predefined set of genes — a biological pathway — is systematically overrepresented among genes that show evidence of differential activity in an experiment. Unlike classical over-representation tests, it encodes prior biological knowledge as a prior distribution and updates it with the observed expression data, yielding posterior probabilities of enrichment rather than p-values. This probabilistic framing naturally handles small samples, multiple pathways, and uncertainty propagation in a coherent statistical framework. | 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. |
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