Table of Contents
VALIDATIONF90
Summary
This program processes solutions obtained with blupf90+ or gibbsf90+ to obtain validation statistics presented in Legarra et al. 2008 and Legarra et al. 2018. Confidence intervals for validation statistics are calculated as in Bermann et al. 2024.
The program works by obtaining solutions with a training (partial) dataset and the complete (whole) dataset. Then, validation statistics are obtained from those solutions and a list of validation individuals.
The steps to do validation with the blupf90 software suite are
- Run renumf90.
- Identify the validation individuals and save a list with their renumbered identifications.
- Create the partial dataset.
- Run validationf90.
Options
OPTION validation eff ids
eff must indicate the effect to validate and ids is the name of a file containing a list of the renumbered identifications of the validation set
OPTION predictive_ability
calculates predictive ability (correlation between predictions and adjusted phenotypes) based on the file yhat_residual obtained from predictf90
OPTION prefix filename
the program reads filename_whole and filename_partial instead of solutions_whole and solutions_partial, respectively
OPTION focal_var mode x
Genetic variance in the validation set. It can be calculated from the inbreeding of the validation set or specified by the user. mode can be inb (default) or usr. When mode is usr, x are the genetic variances in the validation set for each trait
OPTION se type
Calculates standard errors (sd) and confidence intervals (ci) for the validation statistics. type can be:
- exact: frequentist sd and ci are calculated. The prediction error variances matrices for each trait are required. They can be obtained by running blupf90+ with OPTION store_pev_pec eff full, where eff is the effect to validate.
- boot: sd and ci are obtained by bootstrapping.