Fit PCA on the training set and apply the same transformation to the test set. The goal is to use principal components in prediction models as a smaller number of variables instead of all the marker predictors.
apply_pca(split, geno, num_pcs = 100, ...)
split | An object of class
|
---|---|
geno |
|
num_pcs |
|
pc_values A data.frame
containing the principal components
in columns and the names of all lines used in the study is contained in the
first column 'geno_ID'. PCs for the lines present in the test set were
computed based on the transformation done on the training set.
Cathy C. Westhues cathy.jubin@uni-goettingen.de