GWAS

Whereas in previous FinnGen releases we used SAIGE for association analysis, we now switched to regenie for release 7. 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 2.0.2 which we modified to include dosage-based calculation of allele frequencies in cases and controls.

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:

• ​3,095 endpoints

• 309,154 samples

• 16,962,023 variants

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