I'm trying to use the bfGWAS tool, which analyses GWAS data and integrates functional annotations to identify casual SNPs (paper and github). In the user manual, it states:

We recommend first regressing covariants out from the original phenotypes, and then provide bfGWAS the corrected phenotypes (i.e., residuals from the regression model with covariates).

I am unclear what this means and how to go about determining the corrected phenotypes. Typically, in an association test with covariates, a regression would be performed using a model like

pheno ~ snp + covariate 

I could then get the residuals from this model. However, I'm not certain how to go about it for all SNPs, and then adjust the phenotypes. I have case-control data, so the phenotypes are binary.