GWAS

We used regenie for release 9. Regenie's main advantages are fast leave-one-chromosome-out relatedness calculation which avoids proximal contamination, and use of an approximate Firth test which gives more reliable effect size estimates for rare variants.

We used regenie version 2.2.4.

Links:

• regenie preprint

• regenie GitHub repository

• FinnGen regenie GitHub repository

• FinnGen regenie pipeline GitHub repository

The Docker image used in the analysis is available in Docker Hub.

We analyzed:

• ​2,272 endpoints

  • 2,269 binary endpoints

  • 3 quantitative endpoints (HEIGHT_IRN, WEIGHT_IRN, BMI_IRN)

• 377,277 samples

  • 210,870 females

  • 166,407 males

• 20,175,454 variants

We included the following covariates in the model: sex, age, 10 PCs, genotyping batch.