Post by ljc on Jan 28, 2016 15:44:43 GMT
Hi
I am running two bivariate analyses. In the first analysis I have Pheno1 (n=2681) and Pheno2 (n=3143). In the second analysis I have Pheno3 (n=1093) and Pheno2. Pheno1 and Pheno2 are observed in separate individuals (i.e. all individuals with a value for Pheno1 have Pheno2 missing) and the same is true for Pheno3 and Pheno2. I am using the same grm in both - one that was calculated from my entire genotyped sample (many more people than I have in my analyses). I am using version: GCTA 1.24.3.
I was expecting the V(G)_tr2 and V(G)/Vp_tr2 to be the same from the two analyses but they're different. I am assuming that since a joint model is run, you would expect a slightly different result but I am getting, for example, V(G)_tr2 0.331550 0.101665 and V(G)_tr2 0.284420 0.099099. I realise my sample size isn't really big enough for this kind of analysis so is this purely a power issue?
Thanks
I am running two bivariate analyses. In the first analysis I have Pheno1 (n=2681) and Pheno2 (n=3143). In the second analysis I have Pheno3 (n=1093) and Pheno2. Pheno1 and Pheno2 are observed in separate individuals (i.e. all individuals with a value for Pheno1 have Pheno2 missing) and the same is true for Pheno3 and Pheno2. I am using the same grm in both - one that was calculated from my entire genotyped sample (many more people than I have in my analyses). I am using version: GCTA 1.24.3.
I was expecting the V(G)_tr2 and V(G)/Vp_tr2 to be the same from the two analyses but they're different. I am assuming that since a joint model is run, you would expect a slightly different result but I am getting, for example, V(G)_tr2 0.331550 0.101665 and V(G)_tr2 0.284420 0.099099. I realise my sample size isn't really big enough for this kind of analysis so is this purely a power issue?
Thanks
