roiNorm: Region of Interest Normalisation

In kylebario/unorm: Urine Normalisation

Description

This function normalises the spectra based on a specific area of the spectra. This is helpful when one region is constant across all spectra.

Usage

roiNorm(X, sh = c(2.5, 2.75))

Arguments

X	A numerical matrix with rows being the spectra and columns being the chemical shift variables
sh	The numerical values defining the lower and upper regions of the Region of Interest. default = c(3,3.1).

Details

How It Works:

1. This function takes the values of the shift argument and finds the integral (or area) of the peak in that chemical shift region in an experimental spectra.

2. Each intensity in that experimental spectra is then divided by that integral to scale it. This method works much like how taNorm() and creNorm() do, except instead of using an entire spectrum's integral or the creatinine peak specifically, you are able to use what ever ppm region you wish.

Advantages:

• Region of Interest Normalisation (ROI) gives the data analyst more control over what region will be used which can be advantageous.

Limitations:

• ROI is also subject to the flaws that impact creatinine normalisation (creNorm()) in that, whatever factors that create variation in the region one chooses, will also impact the entire spectrum's state.

• Reference-based normalisations may provide more robust normalisation.

Value

This function returns a list with:

1. The normalised X matrix, and

2. A numerical array of the corresponding dilution factors.

• Following the example below will extract the results quickly and easily.

Author(s)

[e-mail]

See Also

A description of Region of Interest Normalisation can be found in this paper: http://dx.doi.org/10.1007/s11306-018-1400-6

Other Attribute-Based: creNorm(), qNorm(), taNorm(), vecNorm()

Examples

data(X)
roiNorm(X, sh = c(1.5,2))
cat(dilf_roi)

kylebario/unorm documentation built on Dec. 21, 2021, 8:45 a.m.