Imputation of missing values using population structure inferred with LEA::snmf

Imputation of missing values using population structure inferred with LEA::snmf

Usage

str_impute(
  gen,
  K,
  entropy = TRUE,
  repetitions = 10,
  project = "new",
  quiet = TRUE,
  save_output = FALSE,
  output_filename = NULL
)

gen: a dosage matrix, an object of class 'vcfR', or an object of type snmfProject
K: An integer vector corresponding to the number of ancestral populations for which the snmf algorithm estimates have to be calculated.
entropy: A boolean value. If true, the cross-entropy criterion is calculated (see create.dataset and cross.entropy.estimation).
repetitions: An integer corresponding with the number of repetitions for each value of K.
project: A character string among "continue", "new", and "force". If "continue", the results are stored in the current project. If "new", the current project is removed and a new one is created to store the result. If "force", the results are stored in the current project even if the input file has been modified since the creation of the project.
quiet: whether to operate quietly and suppress the results of cross-entropy scores (defaults to TRUE; only does so if more than one K-value); only displays run with minimum cross-entropy
save_output: if TRUE, saves SNP GDS and ped (plink) files with retained SNPs in new directory; if FALSE returns object (defaults to FALSE)
output_filename: if save_output = TRUE, name prefix for saved .geno file, sNMF project file, and sNMF output file results (defaults to FALSE, in which no files are saved)

dosage matrix with imputed missing values