All samples were genotyped with the Affymetrix Human SNP Array 6.0. Hybridization of genomic DNA was done in accordance with the manufacturer’s standard recommendations. Genotypes were determined using Birdseed2 clustering algorithm (Affymetrix Array 6.0). For quality control purposes, we applied a positive control and a negative control DNA every 96 samples. On the chip level, only subjects with overall genotyping efficiencies of at least 93% were included. In addition, the called sex had to agree with the sex in the KORA study database. Imputation of genotypes was performed with IMPUTE v.0.4.2 software based on HapMap II.
Array 6
Manufactured by Thermo Fisher Scientific
The Array 6.0 is a versatile laboratory instrument designed for various analytical applications. It provides a platform for high-throughput, multi-analyte detection and quantification. The core function of the Array 6.0 is to enable efficient and accurate data collection for scientific research and analysis.
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Lab products found in correlation
2 protocols using array 6
1
Affymetrix Human SNP Array 6.0 Genotyping
2
Genome-Wide Genotyping and Imputation
Check if the same lab product or an alternative is used in the 5 most similar protocols
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The 3,368 patients were genotyped on Affymetrix Genome-Wide Human SNV Array 5.0 or on Array 6.0 at the CRCHUM Genomic Platform. Only those SNPs with greater than 90% call rate were included in the analysis and only those SNPs that were in Hardy-Weinberg equilibrium at a p-value > 10 -3 were kept for analysis. Additional SNPs were imputed for each array using the IMPUTE2 program 27 and the 100 genome CEU linkage disequilibrium (LD) reference panel. Only those SNPs with an imputation score greater than 0.80 were retained. A subset (147,088) of the genome wide genotyped SNPs that were not in LD (defined as r 2 ≤0.8) was selected to perform a principal component (PC) analysis with Eigenstrat software 28 to test for population stratification within the Caucasian population samples. The first 2 independent PCs from this analysis (PC1 and PC2), were subsequently considered as covariates in association analysis to correct for population stratification.
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