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Perform simple imputation on rows of a matrix

Source: R/utils.R
impute.Rd

Impute NA values for each row of a matrix.

Usage

impute(x, fun = median)

Arguments

x

numeric matrix or data.frame that can be converted to a numeric matrix

fun

Imputation function to apply to rows of the matrix. Default median

Value

Matrix with imputed values

Examples

# Create a matrix of values with NAs
X <- matrix(runif(25), 5, dimnames = list(paste0("CpG", 1:5), paste0("Sample", 1:5)))
X[sample.int(25, 5)] <- NA
X
#>          Sample1   Sample2   Sample3    Sample4    Sample5
#> CpG1          NA 0.7403324 0.1575701         NA 0.09950194
#> CpG2 0.872853523 0.5677240 0.1141094 0.09897127 0.78451347
#> CpG3 0.672521725 0.1186733 0.1891373 0.06796681 0.21496728
#> CpG4 0.004080585        NA 0.8993360         NA         NA
#> CpG5 0.265511174 0.6003532 0.3032485 0.08691927 0.36929772

# Impute missing values with row medians
impute(X)
#>          Sample1   Sample2   Sample3    Sample4    Sample5
#> CpG1 0.157570087 0.7403324 0.1575701 0.15757009 0.09950194
#> CpG2 0.872853523 0.5677240 0.1141094 0.09897127 0.78451347
#> CpG3 0.672521725 0.1186733 0.1891373 0.06796681 0.21496728
#> CpG4 0.004080585 0.4517083 0.8993360 0.45170827 0.45170827
#> CpG5 0.265511174 0.6003532 0.3032485 0.08691927 0.36929772

# Impute missing values with arbitrary function
impute(X, fun = function(x) { -1} )
#>           Sample1    Sample2   Sample3     Sample4     Sample5
#> CpG1 -1.000000000  0.7403324 0.1575701 -1.00000000  0.09950194
#> CpG2  0.872853523  0.5677240 0.1141094  0.09897127  0.78451347
#> CpG3  0.672521725  0.1186733 0.1891373  0.06796681  0.21496728
#> CpG4  0.004080585 -1.0000000 0.8993360 -1.00000000 -1.00000000
#> CpG5  0.265511174  0.6003532 0.3032485  0.08691927  0.36929772