creNorm: Creatinine Normalisation

In kylebario/concentr8r: MRS Data Preprocessing and Normalisation

Creatinine Normalisation

Description

Creatinine Normalisation (CN) is a useful method much like region of interest normalisation that can normalise spectra based on the total area of the creatinine signal at the chemical shift 3.05ppm.

Usage

creNorm(X, ppm = NULL, cre3 = c(3, 3.1), cre4 = c(4, 4.1), err = 5)

Arguments

X	The spectra intended to be normalised. Can either be a single spectrum in the form of a numerical array or multiple spectra in a numerical matrix with the rows being the spectra/samples and the columns being the ppm variables
ppm	A numerical array holding the chemical shift values of the X matrix. Only necessary when X is an array, not when X is a matrix
cre3	A concatenated numerical value of the lower and upper ppm values where the creatinine peak at 3.05 starts and ends.
cre4	A concatenated numerical value of the lower and upper ppm values where the creatinine peak at 4.05 starts and ends.
err	The level of error given when calculating the creatinine peak ratios. interperted as a percentage (i.e., 5 = 5%)

Details

creNorm() works by dividing each element in a row with the sum of the values from its Creatinine signal.

Value

This function assigns the normalised X argument (as X_cre) and the calculated dilution factors (as dilf_cre) to the global environment.

Author(s)

[e-mail]

See Also

More on the methodology of CN and issue with using it are outlined here: https://doi.org/10.1021/ac051632c

Other Attribute-Based: q1Norm(), roiNorm(), taNorm(), vecNorm()

Examples

# When X contains multiple spectra, ppm is not required
data(X, ppm)
creNorm(X)
cat(dilf_cre)

# When X has only one spectrum, ppm is required
data(X, ppm)
creNorm(X[1,], ppm)
cat(dilf_cre)

kylebario/concentr8r documentation built on Nov. 9, 2022, 12:47 a.m.