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| Filoģenētiskā laika sēriju analīze× | Ģenoma plaša asociācijas pētījums (GWAS)× | |
|---|---|---|
| Nozare | Bioinformātika | Bioinformātika |
| Saime | Process / pipeline | Process / pipeline |
| Izcelsmes gads≠ | 2000s (molecular clock methods earlier; BEAST framework 2007) | 2005–2007 |
| Autors≠ | Alexei J. Drummond, Andrew Rambaut, and colleagues | Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007) |
| Tips≠ | Evolutionary bioinformatics pipeline | Observational genomic association study |
| Pirmavots≠ | Drummond, A. J., & Rambaut, A. (2007). BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evolutionary Biology, 7, 214. 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 ↗ |
| Citi nosaukumi | temporal phylogenetics, time-resolved phylogenetics, molecular clock phylogenetics, phylodynamics | GWAS, genome-wide association analysis, whole-genome association study, WGAS |
| Saistītās | 6 | 6 |
| Kopsavilkums≠ | Time-series phylogenetic analysis reconstructs the evolutionary history of organisms or genetic variants using sequences sampled at known time points. By incorporating sampling dates directly into the model, it estimates divergence times, substitution rates, and ancestral relationships on an absolute timescale — making it essential for studying viral outbreaks, ancient DNA dynamics, and rapid microbial evolution. | 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. |
| ScholarGateDatu kopa ↗ |
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