Compară metode

	Analiza Filogenetică Bazată pe Rețele	Studiu de asociere la nivel de genom (GWAS)
Domeniu	Bioinformatică	Bioinformatică
Familie	Process / pipeline	Process / pipeline
Anul apariției	1992–2004 (foundational algorithms); broader development 1990s–2010s	2005–2007
Autorul original	Hans-Jürgen Bandelt & Andreas Dress (split decomposition); David Bryant & Vincent Moulton (Neighbor-Net)	Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007)
Tip	Computational phylogenetic method	Observational genomic association study
Sursa seminală	Bandelt, H.-J., & Dress, A. W. M. (1992). Split decomposition: A new and useful approach to phylogenetic analysis of distance data. Molecular Phylogenetics and Evolution, 1(3), 242–252.	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.
Denumiri alternative	phylogenetic network, reticulate phylogenetics, split network analysis, evolutionary network inference	GWAS, genome-wide association analysis, whole-genome association study, WGAS
Înrudite	6	6
Rezumat	Network-based phylogenetic analysis constructs graph-structured representations of evolutionary relationships that explicitly accommodate reticulate events — including hybridization, horizontal gene transfer, recombination, and incomplete lineage sorting — which strictly bifurcating phylogenetic trees cannot represent. Instead of forcing sequences into a single bifurcating tree, the method infers splits or reticulations in the data and visualises them as a network, revealing conflicting phylogenetic signals that are biologically informative.	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.