Hello, we have dataset with repeated measurements on the same animal at differenet stages. And according to a previous post and Supplementary Table 8 from Yang et al. 2011, it seems GCTA can also handle the reapeated measurements using a repeatability model. Then we can try different ways to build up the 1st (for additive genetic effect) and 2nd GRM (for PE).
1. we keep the GRM produced from GCTA as 1st GRM and add the 2nd GRM as identity matrix for PE. But it was not invertible. 2. we went through the paper again, and found out perhaps we should define matrices with dimension of #observations x #observations and put the relationship between same animal as 1 (or can be around 1 for GRM). but then there are linear dependencies in the matrices, we would expect not invertiable matrices.
I am just wondering how did you fit the two customised GRMs in the paper.