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GWAS בייסיאני×מחקר השוואתי של כלל הגנום (GWAS)×
תחוםביואינפורמטיקהביואינפורמטיקה
משפחהProcess / pipelineProcess / pipeline
שנת המקור2007–2009 (formal statistical framework)2005–2007
הוגה השיטהMatthew Stephens, David J. Balding, Jon Wakefield (key formalizers ca. 2007–2009)Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007)
סוגStatistical genetic association analysisObservational genomic association study
מקור מכונןStephens, M., & Balding, D. J. (2009). Bayesian statistical methods for genetic association studies. Nature Reviews Genetics, 10(10), 681–690. DOI ↗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. link ↗
כינוייםBayesian GWAS, Bayesian genome-wide association analysis, Bayesian GWA study, BF-GWASGWAS, genome-wide association analysis, whole-genome association study, WGAS
קשורות56
תקצירBayesian GWAS applies Bayesian statistical inference to genome-wide association studies, replacing classical p-value thresholds with Bayes factors and posterior probabilities. This framework naturally incorporates prior knowledge about effect sizes and variant frequencies, quantifies evidence for association on a continuous scale, and supports principled fine-mapping of causal variants within associated loci. It is widely used in complex trait genetics, population genomics, and translational research where uncertainty quantification and multi-variant modeling matter.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.
ScholarGateמערך נתונים
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  2. 2 מקורות
  3. PUBLISHED
  1. v1
  2. 2 מקורות
  3. PUBLISHED

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ScholarGateהשוואת שיטות: Bayesian GWAS · Genome-wide association study. אוחזר בתאריך 2026-06-18 מתוך https://scholargate.app/he/compare