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Chunk #7 — Materials and Methods — Analysis of WTCCC Type 1 and Type 2 Diabetes Data Under Heterogeneity

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The impact of phenotypic and genetic heterogeneity on results of genome wide association studies of complex diseases.
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A number of quality control (QC) steps were performed on this data in the original WTCCC GWAS study [24]. Individuals and SNPs that were retained had passed each of the following exclusion criteria: 1) missing data rate>3% per sample across all SNPs; 2) heterozygosity>30% or <23%; 3) discrepancies in ID information; 4) ancestry control (outliers after multi-dimensional scaling); 5) duplicated samples (identity>99%); 6) relatedness (86%–96% identity); 7) missing data rate>5% per SNP; 8) missing data rate>1% when MAF<5%; 9) Hardy-Weinberg exact p-value<5.7×10−7 (in 2,938 controls) [24].