I am currently working with some imputed genotype data and hope you could help me with a few questions regarding after-imputation quality control.
I have filtered out SNPs with low imputation quality (r2<0.8). However, while running the GWAS association analysis using GEMMA I have noticed that some SNPs are being filtered out with default filtering thresholds within the software (such as MAF and SNP-level missingness). Should any additional QC steps (in addition to filtering poorly imputed SNPs) be applied after imputation before running the GWAS? Based on the literature, it seems that only imputation quality thresholds are applied after imputation, however, high missingness rate seems quite problematic...
Any help would be really appreciated.