# Association tests ## Endpoint We included ​​**3,095**​ endpoints in the analysis. Endpoints with less than 80 cases or less than 1,000 controls among the **309,154** samples were excluded, as well as endpoints labeled with an OMIT tag in the endpoint definition file. ## Null models For regenie step 1 LOCO prediction computation for each endpoint, we used age, sex, 10 PCs, Finngen 1 or 2 chip or legacy genotyping batch as covariates. The null model didn’t initially converge for three phenotypes: L12\_ALOPECANDRO, DRY\_AMD and N14\_ENDOMETRIOSIS\_FALLOPIAN\_TUBE. For the first two, we excluded legacy batches with less than 10 cases from covariates and for N14\_ENDOMETRIOSIS\_FALLOPIAN\_TUBE, we excluded all legacy batches from covariates, and the nulls converged successfully. For calculating genetic relatedness in regenie step 1, we included variants 1) imputed with an INFO score > 0.95 in all batches and 2) > 97 % non-missing genotypes and 3) MAF > 1 %. The remaining variants were LD pruned with a 1Mb window and r2 threshold of 0.1. This resulted in a set of 55,139 well-imputed not rare variants for relatedness calculation. We used a genotype block size of 1,000 in regenie step 1. ## Association tests We ran association tests with regenie for each of the 3,095 endpoints for each variant with a minimum allele count of 5 among each phenotype’s cases and controls. We used the approximate Firth test for variants with an initial p-value of less than 0.01 and computed the standard error based on effect size and likelihood ratio test p-value (regenie options --firth --approx --pThresh 0.01 --firth-se). --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://finngen.gitbook.io/documentation/r7/methods/phewas/logistic-regression.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.