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Bayesianische Kopienzahlvariationsanalyse×Genomweite Assoziationsstudie (GWAS)×
FachgebietBioinformatikBioinformatik
FamilieProcess / pipelineProcess / pipeline
Entstehungsjahr2004–20072005–2007
UrheberColella et al. (QuantiSNP); Fridlyand et al. (HMM-based Bayesian CNV)Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007)
TypProbabilistic genomic analysis pipelineObservational genomic association study
Wegweisende QuelleColella, S., Yau, C., Taylor, J. M., Mirza, G., Butler, H., Clouston, P., Bassett, A. S., Seller, A., Holmes, C. C., & Ragoussis, J. (2007). QuantiSNP: an Objective Bayes Hidden-Markov Model to detect and accurately map copy number variation using SNP genotyping data. Nucleic Acids Research, 35(6), 2013–2025. 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 ↗
AliasnamenBayesian CNV analysis, Bayesian CNV calling, probabilistic CNV detection, Bayesian HMM-CNVGWAS, genome-wide association analysis, whole-genome association study, WGAS
Verwandt66
ZusammenfassungBayesian copy number variation (CNV) analysis is a probabilistic framework for detecting genomic segments where an individual's DNA copy count deviates from the diploid norm. By placing prior distributions over copy-number states and updating them with array CGH, SNP array, or sequencing read-depth evidence, the approach yields posterior probabilities for each copy-number state along the genome, providing statistically principled uncertainty quantification that frequentist segmentation methods lack.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.
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ScholarGateMethoden vergleichen: Bayesian Copy Number Variation Analysis · Genome-wide association study. Abgerufen am 2026-06-18 von https://scholargate.app/de/compare