Post by mbilow on Oct 19, 2015 2:49:03 GMT
I'm running some computations using GCTA and I'm finding some differences on the order of 1-2% in some of my Vp calculations and the ones returned by GCTA using a single fixed effect environmental factor for GxE analysis.
Setting:
Y = 1 x M quantitative phenotype (uncentered)
x_e = 1 x M environmental variable (the only fixed effect)
X_e = 2 x M matrix where the first column is all 1's and the second column is x_e
b_e = (X_e^T . X_e)^(-1) *(X_e^T . Y)
The variance of (Y - X_e . b_e)--estimated with M degrees of freedom--is very close, but not quite the same as the V_p I get in the .hsq file by running:
gcta64 --reml --reml-maxit 10000 --reml-alg 2 --reml-no-lrt --grm {plink} --pheno {pheno} --gxe {gxe} --reml-lrt 2 --out {pheno}
Is there a step somewhere that the fixed effect (b_e) is getting re-estimated? Looking on page 77 of the AJHG 2011 paper in the second column, it appears that V_p is assumed to be known before the REML iterations, since the initial estimates for the variance components are based on V_p.
Setting:
Y = 1 x M quantitative phenotype (uncentered)
x_e = 1 x M environmental variable (the only fixed effect)
X_e = 2 x M matrix where the first column is all 1's and the second column is x_e
b_e = (X_e^T . X_e)^(-1) *(X_e^T . Y)
The variance of (Y - X_e . b_e)--estimated with M degrees of freedom--is very close, but not quite the same as the V_p I get in the .hsq file by running:
gcta64 --reml --reml-maxit 10000 --reml-alg 2 --reml-no-lrt --grm {plink} --pheno {pheno} --gxe {gxe} --reml-lrt 2 --out {pheno}
Is there a step somewhere that the fixed effect (b_e) is getting re-estimated? Looking on page 77 of the AJHG 2011 paper in the second column, it appears that V_p is assumed to be known before the REML iterations, since the initial estimates for the variance components are based on V_p.
