I am doing meta-analysis using GWAMA. However, I had a query. My data which I want to meta-analyze looks this
SNP CHR POS STR IMP EA NEA BETA SE P r2-hat r2-min rs12562034 1 768448 + minimac A G 4.9606e-02 4.8640e-01 3.0588e-01 0.9871 0.98237
All of the SNPs in my data is imputed using minimac, however the imputation score (r2-Hat) for some is high. The input file for GWAMA requires to have encoded for imputation using 0(not imputed) or 1(imputed) else it considers all SNPs to be genotyped.
My question is will it be ok to define a threshold, for example, those SNPs having r2 > 0.9 be considered as genotyped (0 in input file) and rest be imputed (1 in input file)? Or some other threshold would be useful? Is this a right way to encode for the SNPs?
I have tried to look for this papers but all I could find was that GWAMA is used, not the details of the imputation encoding.
Your help would be appreciated. Thanks.