Having used REML to estimate proportions of variance explained by one or more kinship matrices, you can then estimate effect sizes for the predictors used to calculate the kinship matrices. The argument for this is

--calc-blups

which requires the following options:

--remlfile <remlfile> - specifies the .reml file produced by REML.

--grm <grmstem> or --mgrm <grmlist> - specifies the kinship matrices used when performing REML.

--bfile/--gen/--sp/--speed <prefix> - specifies the data files used when calculating the kinship matrices (if regions were used when performing REML, these data files must also include the regional predictors).

_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

The output file are

<output>.blup - contains the overall estimates of effect sizes for each predictor. The first four columns provide the predictor name, Allele 1 (test allele), Allele 2 (reference allele) and the predictor centre (the mean of its allele count with respect to Allele 1), with the final column providing the (raw) effect size. To work out the contribution of a predictor, subtract from its value the centre then multiply this by the effect size.

<output>.blup.full - for each predictor, this indicates how much each kinship matrix and region contributes to its overall effect size estimate (as most predictors will contribute to only one kinship matrix or region, this file will contain many zeros).

<output>.pred and <output>.pred.full - contains the predicted values for each individual, either overall or divided into contributions from kinship matrices and regions.

_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _

Example: for this we use the binary PLINK files test.bed, test.bim and test.fam available in the Test Datasets, and results from the example in REML.

../ldak.out --calc-blups res1 --remlfile res1.reml --grm partitions/kinships.all --bfile test