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. 2017 Dec 30;109(3):497–506. doi: 10.1111/cas.13463

Figure 1.

Figure 1

Summary workflow of genome‐wide association studies (GWAS). GWAS starts from the determination of phenotypes. Genomic DNA extracted from samples was genotyped with chips that contained up to hundreds of thousands of single nucleotide polymorphisms (SNP). Quality control (QC) was carried out on samples and SNP before association studies. Sample quality control includes: (1) sample quality to exclude poorly genotyped samples; (2) identity‐by‐state analysis to exclude close relatedness samples; and (3) principal component analysis to evaluate population stratification of the sample sets to obtain a homogeneous sample set before carrying out the association study. SNP QC were set to exclude SNP if: (1) they were of low genotype quality; (2) if SNP deviated from normal distribution by evaluating the Hardy‐Weinberg equilibrium in control samples; and (3) if they contained non‐polymorphic SNP (minor allele frequency = 0). To evaluate the association distribution, quantile‐quantile plots (Q‐Q plot) of observed P‐value vs expected P‐value and genomic inflation factor (λ value) were evaluated to eliminate the possibility of population substructure. Manhattan plots of P‐value (−log10) vs chromosome loci were used to depict an overview of the GWAS, with each dot representing a SNP and each color representing a chromosome. Post‐GWAS included: (A) a meta‐analysis that combined multiple studies to identify significantly associated SNP; and (B) functional analysis. Two of the most common functional analyses of the identified variants are: (i) electrophoretic mobility shift assay (EMSA) to check the existence of proteins, mainly transcription factors, binding to SNP‐contained DNA fragments; and (ii) luciferase reporter assay (comparison of relative luciferase activity) to assess the associated SNP that could affect differential gene expression (as shown in the figure). (C) Other analyses, including gene‐based analysis, pathway analysis, polygenic risk estimation, SNP‐SNP interaction, SNP‐environment interaction etc. could be carried out after GWAS