R/mutate_rsd.R
mutate_rsd.RdThis function adds a new column to the variable_info slot of a mass_dataset object,
which contains the relative standard deviation (RSD) for each variable according to the samples specified.
mutate_rsd(object, according_to_samples = "all")A mass_dataset object.
A character vector specifying the sample IDs to consider when calculating the RSD. Default is "all", which considers all samples.
A modified mass_dataset object with an updated variable_info slot.
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: 1.0.28
#> --------------------
#> 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() 2023-10-01 23:24:33
##calculate RSDs according to all the samples
object =
mutate_rsd(object = object)
object
#> --------------------
#> massdataset version: 1.0.28
#> --------------------
#> 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 4 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:[ 4 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() 2023-10-01 23:24:33
#> mutate_rsd ----------
#> Package Function.used Time
#> 1 massdataset mutate_rsd() 2023-10-01 23:24:33
head(extract_variable_info(object))
#> variable_id mz rt rsd
#> M136T55_2_POS M136T55_2_POS 136.06140 54.97902 50.756560
#> M79T35_POS M79T35_POS 79.05394 35.36550 28.257007
#> M307T548_POS M307T548_POS 307.14035 547.56641 35.041286
#> M183T224_POS M183T224_POS 183.06209 224.32777 1.224228
#> M349T47_POS M349T47_POS 349.01584 47.00262 27.715030
#> M182T828_POS M182T828_POS 181.99775 828.35712 25.534063
##calculate RSDs according to only QC samples
object =
mutate_rsd(object = object,
according_to_samples =
get_sample_id(object)[extract_sample_info(object)$class == "QC"])
object
#> --------------------
#> massdataset version: 1.0.28
#> --------------------
#> 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() 2023-10-01 23:24:33
#> mutate_rsd ----------
#> Package Function.used Time
#> 1 massdataset mutate_rsd() 2023-10-01 23:24:33.342529
#> 2 massdataset mutate_rsd() 2023-10-01 23:24:33.368802
head(extract_variable_info(object))
#> variable_id mz rt rsd rsd.1
#> M136T55_2_POS M136T55_2_POS 136.06140 54.97902 50.756560 40.05551
#> M79T35_POS M79T35_POS 79.05394 35.36550 28.257007 51.97966
#> M307T548_POS M307T548_POS 307.14035 547.56641 35.041286 28.26044
#> M183T224_POS M183T224_POS 183.06209 224.32777 1.224228 NA
#> M349T47_POS M349T47_POS 349.01584 47.00262 27.715030 50.95194
#> M182T828_POS M182T828_POS 181.99775 828.35712 25.534063 NA