impute_snp_data: A function to impute SNP data

In plmmr: Penalized Linear Mixed Models for Correlated Data

A function to impute SNP data

Description

A function to impute SNP data

Usage

impute_snp_data(
  obj,
  X,
  impute,
  impute_method,
  parallel,
  outfile,
  quiet,
  seed = as.numeric(Sys.Date()),
  ...
)

Arguments

obj	a bigSNP object (as created by read_plink_files())
X	A matrix of genotype data as returned by name_and_count_bigsnp
impute	Logical: should data be imputed? Default to TRUE.
impute_method	If 'impute' = TRUE, this argument will specify the kind of imputation desired. Options are: mode (default): Imputes the most frequent call. See bigsnpr::snp_fastImputeSimple() for details. random: Imputes sampling according to allele frequencies. mean0: Imputes the rounded mean. mean2: Imputes the mean rounded to 2 decimal places. xgboost: Imputes using an algorithm based on local XGBoost models. See bigsnpr::snp_fastImpute() for details. Note: this can take several minutes, even for a relatively small data set.
parallel	Logical: should the computations within this function be run in parallel? Defaults to TRUE. See count_cores() and ?bigparallelr::assert_cores for more details. In particular, the user should be aware that too much parallelization can make computations slower.
outfile	Optional: the name (character string) of the prefix of the logfile to be written. Defaults to 'process_plink', i.e. you will get 'process_plink.log' as the outfile.
quiet	Logical: should messages be printed to the console? Defaults to TRUE
seed	Numeric value to be passed as the seed for impute_method = 'xgboost'. Defaults to as.numeric(Sys.Date())
...	Optional: additional arguments to bigsnpr::snp_fastImpute() (relevant only if impute_method = "xgboost")

Value

Nothing is returned, but the obj$genotypes is overwritten with the imputed version of the data

plmmr documentation built on April 4, 2025, 12:19 a.m.