Chunk #25 — Materials and Methods — Estimating SNP heritability and CGR

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Meta-GWAS Accuracy and Power (MetaGAP) Calculator Shows that Hiding Heritability Is Partially Due to Imperfect Genetic Correlations across Studies.

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Using 1000-Genomes imputed data from the RS, STR, and HRS, we estimate SNP-based heritability and CGR respectively by means of univariate and bivariate GREML [36, 37] as implemented in GCTA [36]. In our analyses we consider the subset of HapMap3 SNPs available in the 1000-Genomes imputed data. In S1 Data we report details on the genotype and phenotype data, as well as our quality control (QC) procedure. After QC we have a dataset, consisting of ≈ 1 million SNPs and ≈ 20,000 individuals, from which we infer hSNP2 and CGR. In S1 Estimation we provide details on the specifications of the models used for GREML estimation.