Fast imputation via mode, mean, sampling according to allele frequencies, or 0.

snp_fastImputeSimple(
Gna,
method = c("mode", "mean0", "mean2", "random", "zero"),
ncores = 1
)

Gna A FBM.code256 (typically $genotypes). You can have missing values in these data. Either "random" (sampling according to allele frequencies), "mean0" (rounded mean), "mean2" (rounded mean to 2 decimal places), "mode" (most frequent call), "zero" (by 0). Number of cores used. Default doesn't use parallelism. You may use nb_cores. ## Value A new FBM.code256 object (same file, but different code). ## See also snp_fastImpute() ## Examples bigsnp <- snp_attachExtdata("example-missing.bed") G <- bigsnp$genotypes
G[, 2]  # some missing values#>   [1] NA NA  0  0  0  0  0  0  0  0  0  0  0  0  0  1  0  0  0  0  0  1  0  1  0
#>  [26]  0  0  0  0  1  0  1  0  0  0  0  1  0  1  0  0  0  0  0  0  0  0  0  1  0
#>  [51]  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0
#>  [76]  0  0  0  0  0  0  1  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0 NA
#> [101]  0  1  0  0  0  0  0  0  1  0  0  0  0  0  0  0  0  0  0 NA  0  0  0  0  0
#> [126]  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  1  0  0  0  0  0 NA  0
#> [151]  1  0  0  0  0  0  0  0  0  0  0 NA  0  0  0  0  0  0  0  0  0  0  1  0  0
#> [176]  0  0  0  0  0  0 NA  0  0  0  0  0  0  0  0  0  0  0  0  1  0  0  1  0  0G2 <- snp_fastImputeSimple(G)
G2[, 2]  # no missing values anymore#>   [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 1
#>  [38] 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#>  [75] 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0
#> [112] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> [149] 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> [186] 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0G[, 2]  # imputed, but still returning missing values#>   [1] NA NA  0  0  0  0  0  0  0  0  0  0  0  0  0  1  0  0  0  0  0  1  0  1  0
#>  [26]  0  0  0  0  1  0  1  0  0  0  0  1  0  1  0  0  0  0  0  0  0  0  0  1  0
#>  [51]  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0
#>  [76]  0  0  0  0  0  0  1  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0 NA
#> [101]  0  1  0  0  0  0  0  0  1  0  0  0  0  0  0  0  0  0  0 NA  0  0  0  0  0
#> [126]  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  0  1  0  0  0  0  0 NA  0
#> [151]  1  0  0  0  0  0  0  0  0  0  0 NA  0  0  0  0  0  0  0  0  0  0  1  0  0
#> [176]  0  0  0  0  0  0 NA  0  0  0  0  0  0  0  0  0  0  0  0  1  0  0  1  0  0G\$copy(code = CODE_IMPUTE_PRED)[, 2]  # need to decode imputed values#>   [1] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 1 0 0 0 0 0 1 0 1 0 0 0 0 1
#>  [38] 0 1 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0
#>  [75] 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 1 0 0
#> [112] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0
#> [149] 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0 0 0 0 0 0 0 0 0 0 0
#> [186] 0 0 0 0 0 0 0 0 0 1 0 0 1 0 0