pmartR (version 2.4.6)

normalize_zero_one_scaling: Scale from zero to one

Description

Perform scaling of data from zero to one.

Usage

normalize_zero_one_scaling(omicsData)

Value

Normalized omicsData object of class 'pepData', 'proData', 'metabData', 'lipidData', 'nmrData', created by as.pepData,

as.proData, as.metabData,

as.lipidData, as.nmrData, respectively.

Arguments

omicsData

an object of the class 'pepData', 'proData', 'metabData', 'lipidData', 'nmrData', created by as.pepData, as.proData, as.metabData, as.lipidData, as.nmrData, respectively.

Author

Rachel Richardson

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.

Examples

if (FALSE) { # requireNamespace("pmartRdata", quietly = TRUE)
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
)
}