# 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](https://www.biorxiv.org/content/10.1101/2020.06.19.162354v2.full.pdf)
* [regenie GitHub repository](https://github.com/rgcgithub/regenie)
* [FinnGen regenie GitHub repository](https://github.com/FINNGEN/regenie)
* [FinnGen regenie pipeline GitHub repository](https://github.com/FINNGEN/regenie-pipelines)

The Docker image used in the analysis is available in [Docker Hub](https://hub.docker.com/r/finngen/regenie).

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.