| normalize_zero_one_scaling {pmartR} | R Documentation |
Scale from zero to one
Description
Perform scaling of data from zero to one.
Usage
normalize_zero_one_scaling(omicsData)
Arguments
omicsData |
an object of the class 'pepData', 'proData', 'metabData',
'lipidData', 'nmrData', created by |
Details
The sample-wise minimum of the features is subtracted from each feature in e_data, then divided by the difference between the sample-wise minimum and maximum of the features to get the normalized data. The location estimates are not applicable for this data and the function returns a NULL list element as a placeholder. The scale estimates are the sample-wise feature ranges. All NA values are replaced with zero.
Value
Normalized omicsData object of class 'pepData', 'proData', 'metabData',
'lipidData', 'nmrData', created by as.pepData,
as.proData, as.metabData,
as.lipidData, as.nmrData, respectively.
Author(s)
Rachel Richardson
Examples
library(pmartRdata)
mymetab <- edata_transform(
omicsData = metab_object,
data_scale = "log2"
)
mymetab <- group_designation(
omicsData = mymetab,
main_effects = "Phenotype"
)
norm_data <- normalize_zero_one_scaling(
omicsData = mymetab
)