Comparer des méthodes

	Alignement de séquences	Étude d'association pangénomique (GWAS)
Domaine	Bio-informatique	Bio-informatique
Famille	Process / pipeline	Process / pipeline
Année d'origine	1970 (global alignment); 1981 (local alignment)	2005–2007
Auteur d'origine	Saul B. Needleman & Christian D. Wunsch (global); Temple F. Smith & Michael S. Waterman (local)	Klein et al. (age-related macular degeneration GWAS, 2005); landmark scale: Wellcome Trust Case Control Consortium (2007)
Type	Computational sequence analysis technique	Observational genomic association study
Source fondatrice	Needleman, S. B., & Wunsch, C. D. (1970). A general method applicable to the search for similarities in the amino acid sequence of two proteins. Journal of Molecular Biology, 48(3), 443–453.	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.
Alias	pairwise alignment, multiple sequence alignment, MSA, sequence comparison	GWAS, genome-wide association analysis, whole-genome association study, WGAS
Apparentées	6	6
Résumé	Sequence alignment is a foundational bioinformatics technique that arranges two or more DNA, RNA, or protein sequences to reveal regions of similarity, infer evolutionary relationships, identify functional domains, and map sequencing reads to reference genomes. It underpins virtually every downstream genomic analysis, from variant calling and gene expression quantification to phylogenetics and structural annotation.	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.