One of the ultimate goals of genomic research is to identify genes underlying traits of our interest, such as yield and disease resistances. With increasing density of genetic markers due to new sequencing technologies, genome-wide association study (GWAS) has become the most efficient approach to map genes controlling phenotypic variations. This workshop is based on the graduate student course – Statistical Genomics taught by Zhiwu Zhang at Washing State University. The course website can be found at the course website. The workshop includes three sections: fundamental, GWAS and post GWAS. The fundamental section covers the essential knowledge and skills of statistics and computer programming (R). GWAS section covers the mechanisms, methods, and computing tools in GWAS. We start from genotypes and pick up some of them as genes to simulate phenotypes. Then we examine how well we can map the genes. Then we vary relevant factors to evaluate their strength and pitfall. We also evolve statistical methods and computing tools all the way to their state of art, including FarmCPU and BLINK methods. The post GWAS section introduce the enrichment of GWAS results and validation through genomic selection. The workshop is beneficial for both experimental design and data analyses by using cutting edge GWAS methods and computing tools. Analytical skills, critical thinking and hand-on operations are emphasized throughout the teaching.