Explain the basic workflow of a Genome-Wide Association Study (GWAS).

GWAS identifies genetic variants associated with traits or diseases across many individuals. Workflow: 1) Sample collection and genotyping - collect DNA, genotype using SNP arrays or WGS. 2) Quality control - filter samples (call rate, relatedness, population stratification) and SNPs (call rate, Hardy-Weinberg equilibrium, minor allele frequency). 3) Population stratification - detect and correct using principal component analysis (PCA) as covariates. 4) Association testing - test each SNP for trait association using regression models (linear for quantitative, logistic for binary traits). Tools: PLINK, GCTA, BOLT-LMM. 5) Multiple testing correction - Bonferroni or permutation testing; genome-wide significance typically p < 5x10^-8. 6) Post-GWAS - fine-mapping, functional annotation, pathway analysis, polygenic risk scores.