Scale from zero to one

Source: R/normalize_zero_one.R

Perform scaling of data from zero to one.

normalize_zero_one_scaling(omicsData)

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.

Value

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

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.

Author

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
)