Mutate Variable NA Count in mass_dataset Object — mutate_variable_na

This function adds a new column to the variable_info slot of a mass_dataset object, which contains the count of NA (Not Available) values for each variable according to the samples specified.

Usage

mutate_variable_na_number(object, according_to_samples = "all")

Arguments

object: A mass_dataset object.
according_to_samples: A character vector specifying the sample IDs to consider when calculating the count of NA values. Default is "all", which considers all samples.

Value

A modified mass_dataset object with an updated variable_info slot.

Author

Xiaotao Shen xiaotao.shen@outlook.com

Examples

data("expression_data")
data("sample_info")
data("variable_info")

object =
  create_mass_dataset(
    expression_data = expression_data,
    sample_info = sample_info,
    variable_info = variable_info
  )

object
#> -------------------- 
#> massdataset version: 0.99.1 
#> -------------------- 
#> 1.expression_data:[ 1000 x 8 data.frame]
#> 2.sample_info:[ 8 x 4 data.frame]
#> 8 samples:Blank_3 Blank_4 QC_1 ... PS4P3 PS4P4
#> 3.variable_info:[ 1000 x 3 data.frame]
#> 1000 variables:M136T55_2_POS M79T35_POS M307T548_POS ... M232T937_POS M301T277_POS
#> 4.sample_info_note:[ 4 x 2 data.frame]
#> 5.variable_info_note:[ 3 x 2 data.frame]
#> 6.ms2_data:[ 0 variables x 0 MS2 spectra]
#> -------------------- 
#> Processing information
#> 1 processings in total
#> create_mass_dataset ---------- 
#>       Package         Function.used                Time
#> 1 massdataset create_mass_dataset() 2026-03-02 09:27:13

##calculate NA number according to all the samples
object2 =
  mutate_variable_na_number(object = object)

colnames(extract_variable_info(object))
#> [1] "variable_id" "mz"          "rt"         
colnames(extract_variable_info(object2))
#> [1] "variable_id" "mz"          "rt"          "na_number"  
extract_variable_info_note(object2)
#>          name     meaning
#> 1 variable_id variable_id
#> 2          mz          mz
#> 3          rt          rt
#> 4   na_number   na_number

##calculate NA number according to only QC samples
object3 <-
  mutate_variable_na_number(object = object2,
                according_to_samples =
              get_sample_id(object)[extract_sample_info(object)$class == "QC"])

object3
#> -------------------- 
#> massdataset version: 0.99.1 
#> -------------------- 
#> 1.expression_data:[ 1000 x 8 data.frame]
#> 2.sample_info:[ 8 x 4 data.frame]
#> 8 samples:Blank_3 Blank_4 QC_1 ... PS4P3 PS4P4
#> 3.variable_info:[ 1000 x 5 data.frame]
#> 1000 variables:M136T55_2_POS M79T35_POS M307T548_POS ... M232T937_POS M301T277_POS
#> 4.sample_info_note:[ 4 x 2 data.frame]
#> 5.variable_info_note:[ 5 x 2 data.frame]
#> 6.ms2_data:[ 0 variables x 0 MS2 spectra]
#> -------------------- 
#> Processing information
#> 2 processings in total
#> create_mass_dataset ---------- 
#>       Package         Function.used                Time
#> 1 massdataset create_mass_dataset() 2026-03-02 09:27:13
#> mutate_variable_na_number ---------- 
#>       Package               Function.used                       Time
#> 1 massdataset mutate_variable_na_number() 2026-03-02 09:27:13.881988
#> 2 massdataset mutate_variable_na_number()   2026-03-02 09:27:13.8845

colnames(extract_variable_info(object3))
#> [1] "variable_id" "mz"          "rt"          "na_number"   "na_number.1"
extract_variable_info_note(object3)
#>          name     meaning
#> 1 variable_id variable_id
#> 2          mz          mz
#> 3          rt          rt
#> 4   na_number   na_number
#> 5 na_number.1 na_number.1