We conducted the GWAS for standing height using the directly genotyped and imputed data in the form that they are made available to researchers, but with a subset of samples. Specifically, we only included samples with all of the following properties: (i) imputation was carried out on them; (ii) in the white British ancestry subset (see above); and (iii) the inferred sex matches the self-reported sex. From this group we selected a set of 344,397 unrelated individuals (Supplementary Information ). For standing height, a further 1,076 individuals were excluded owing to missing values for the phenotype, leaving a total of 343,321 for association testing.
We used the software BOLT-LMM (v2.2)46 (link) to look for evidence of statistical association between each marker and standing height. We report association statistics based on a linear mixed model (BOLT-LMM-inf), with the following covariates: (i) array (UK BiLEVE Axiom Array or UK Biobank Axiom Array); (ii) sex (inferred); (iii) age when attended UK Biobank assessment centre; and (iv) principal components 1–20.
The principal components scores were computed using only individuals within the white British ancestry subset, but otherwise with the same method as described above. We conducted tests using the genotype and imputed data files separately.
We used the software BOLT-LMM (v2.2)46 (link) to look for evidence of statistical association between each marker and standing height. We report association statistics based on a linear mixed model (BOLT-LMM-inf), with the following covariates: (i) array (UK BiLEVE Axiom Array or UK Biobank Axiom Array); (ii) sex (inferred); (iii) age when attended UK Biobank assessment centre; and (iv) principal components 1–20.
The principal components scores were computed using only individuals within the white British ancestry subset, but otherwise with the same method as described above. We conducted tests using the genotype and imputed data files separately.
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