# GWAS

We used the SAIGE software for running R6 GWAS as we did in previous releases. SAIGE is a mixed model logistic regression R/C++ package. We used code of version 0.39.1: [https://github.com/weizhouUMICH/SAIGE/tree/finngen\_r6\_jk<br>](https://github.com/weizhouUMICH/SAIGE/tree/finngen_r6_jk) We made two modifications to SAIGE 0.39.1 codebase (neither modification affects the method):

* Null model .rda objects are trimmed to reduce RAM consumption
* Ref hom, het, and alt hom counts in cases and controls are included in the output, summing the probabilities of each genotype over individuals, different from the 0.39.1 implementation in SAIGE in which the counts are sums of most probable genotypes over individuals

We analyzed:

* ​2,861 endpoints
* 260,405 samples
* 16,962,023 variants

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


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