Impute missing values by replacing them with the Feature 'Limit of Detection'

Replace missing intensity values (NA) by what is assumed to be the detector limit of detection (LoD). It is estimated by dividing the Feature minimum by the provided denominator, usually 5. See the References section for more information.

Usage

impute_lod(data, div_by = 5)

Arguments

data: A tidy tibble created by read_featuretable.
div_by: A numeric value that specifies by which number the Feature minimum will be divided

Value

A tibble with imputed missing values.

References

LoD on OmicsForum

Examples

toy_metaboscape %>%
  impute_lod()
#> # A tibble: 110 × 8
#>      UID Feature                Sample  Intensity    RT `m/z` Name       Formula
#>    <int> <chr>                  <chr>       <dbl> <dbl> <dbl> <chr>      <chr>  
#>  1     1 161.10519 Da 26.98 s   Sample1       4    0.45  162. NA         C7H15N…
#>  2     2 276.13647 Da 27.28 s   Sample1       3    0.45  277. Octyl hyd… C16H22…
#>  3     3 304.24023 Da 32.86 s   Sample1       0.2  0.55  305. Arachidon… C20H32…
#>  4     4 417.23236 Da 60.08 s   Sample1       5    1     418. NA         NA     
#>  5     5 104.10753 Da 170.31 s  Sample1       5    2.84  105. NA         C5H14NO
#>  6     6 105.04259 Da 199.80 s  Sample1       5    3.33  106. NA         C3H8NO3
#>  7     7 237.09204 Da 313.24 s  Sample1       1.4  5.22  238. Ketamine   C13H16…
#>  8     8 745.09111 Da 382.23 s  Sample1       3    6.37  746. NADPH      C21H30…
#>  9     9 427.02942 Da 424.84 s  Sample1       4    7.08  428. ADP        C10H15…
#> 10    10 1284.34904 Da 498.94 s Sample1       0.4  8.32 1285. NA         NA     
#> # ℹ 100 more rows