prep.norm: Normalization

In mdatools: Multivariate Data Analysis for Chemometrics

Normalization

Description

Normalizes signals (rows of data matrix).

Usage

prep.norm(data, type = "area", col.ind = NULL, ref.spectrum = NULL)

Arguments

data	a matrix with data values
type	type of normalization "area", "length", "sum", "snv", "is", or "pqn".
col.ind	indices of columns (can be either integer or logical valuws) for normalization to internal standard peak.
ref.spectrum	reference spectrum for PQN normalization, if not provided a mean spectrum for data is used

Details

The "area", "length", "sum" types do preprocessing to unit area (sum of absolute values), length or sum of all values in every row of data matrix. Type "snv" does the Standard Normal Variate normalization, similar to prep.snv. Type "is" does the normalization to internal standard peak, whose position is defined by parameter 'col.ind'. If the position is a single value, the rows are normalized to the height of this peak. If 'col.ind' points on several adjucent vales, the rows are normalized to the area under the peak - sum of the intensities.

The "pqn" is Probabilistic Quotient Normalization as described in [1]. In this case you also need to provide a reference spectrum (e.g. mean or median of spectra for some reference samples). If reference spectrum is not provided it will be computed as mean of the spectra to be preprocessed (parameter data).

Value

data matrix with normalized values

References

1. F. Dieterle, A. Ross, H. Senn. Probabilistic Quotient Normalization as Robust Method to Account for Dilution of Complex Biological Mixtures. Application in 1 H NMR Metabonomics. Anal. Chem. 2006, 78, 4281–4290.

mdatools documentation built on Aug. 13, 2023, 1:06 a.m.