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This lecture series focuses on advanced methods in genome-wide association studies (GWAS) and statistical genetics, with an emphasis on analyzing and modeling complex traits using summary-level genomic data. Students are introduced to practical workflows for preparing and formatting GWAS data, including quality control steps and tools such as munging functions. The series then explores key analytical techniques like linkage disequilibrium score regression (LDSC), multivariate GWAS, and GWAS-by-subtraction, highlighting how genetic relationships between traits can be estimated. It also introduces structural equation modeling (SEM) and its application in Genomic SEM to model the shared genetic architecture of multiple traits.