paperKB
coga / coga-kb
Help
Sign in

Chunk #21 — METHODS — Meta-analysis and fine-mapping with GIANT and UKB50k. — Meta-analysis.

Source
Genetic analyses of diverse populations improves discovery for complex traits.
Embedded
yes

Text

We also conducted a meta-analysis with 50,000 randomly sampled ‘White British’ individuals from the UK Biobank (UKB50k) for comparison. GWAS for both PAGE and UKB50k were estimated with analogous models for BMI and height traits. Within PAGE and UKB50k, we used the inverse normally transformed residuals for each trait by sex and race/ethnicity, and adjusted for population substructure, age, centre and racial/ethnic groups (if applicable). These methods were similar those used by GIANT, using inverse-normal-adjusted residuals for each trait outcome. We then separately meta-analysed results using a fixed-effects model for either PAGE or UKB50k combined with GIANT using the METAL software43. We retained only variants available across both the combined meta-analyses (for PAGE + GIANT or UKB50k + GIANT), which led to the inclusion of approximately 2.5 million variants. Significance was defined as P < 5 × 10−8. Novelty of a locus was defined as ±500 kb from any known loci for the respective trait based on the previously published GIANT data23,24. We also required the at least two SNPs within a 1-Mb results had P < 1 × 10−5 to be retained as a significant known or novel locus.