SCANT: SCAle, Normalize and Transform a data matrix

In speaq: Tools for Nuclear Magnetic Resonance (NMR) Spectra Alignment, Peak Based Processing, Quantitative Analysis and Visualizations

SCAle, Normalize and Transform a data matrix

Description

This function allows the column-wise or row-wise scaling, normalization and transformation operations on a data matrix.

Usage

SCANT(data.matrix, type = "unit", feature_orientation = "columns")

Arguments

data.matrix	the data matrix to be scaled, normalized or transformed.
type	the operations to be performed, this can be multiple and are performed sequentially. Any of 'unit', 'pareto', 'log10', 'log2', 'center', 'range', 'vast', or 'max' are accepted.
feature_orientation	default = "columns". This corresponds to the default feature matrix with samples as rows and features as columns. The other option is "rows": samples as columns and different features as different rows.

Value

The scaled, normalized and/or transformed matrix.

Author(s)

Charlie Beirnaert, [e-mail]

References

van den Berg RA, Hoefsloot HCJ, Westerhuis JA, et al. Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics 2006; 7:142.

Examples

Samples <- 10
Features <- 20
data.matrix <- matrix(runif(n=Features*Samples, min=0,max=100), 
ncol = Features, nrow = Samples) 

changed_matrix = SCANT(data.matrix, type=c('pareto', 'center'), feature_orientation = 'columns')

speaq documentation built on May 23, 2022, 5:06 p.m.