Normalize Spectral Intensity by Root Mean Square

Called internally by normSpectra. Normalizes the intensity data of each input spectrum by dividing each peak's intensity by RMS error. Capable of normalizing 6 spectra to the same m/z value at once.

norm_RMS(dat, mass_dat, spectra_cols)

Arguments

dat	The name of the spectral data frame, containing m/z data in the first column and spectral intensity data in subsequent columns.
mass_dat	A character string; the name of the column in dat containing the m/z data for the spectrum.
spectra_cols	A character string; the names of the column in dat containing the intensity data for the spectrs to be analyzed.

Value

Returns a new data frame including the original m/z data and normalized intensity data.

References

https://github.com/wesleyburr/subMaldi

Author

Kristen Yeh <kristenyeh@trentu.ca> Wesley Burr <wesleyburr@trentu.ca>

See also

normSpectra

Examples

## Load sample dataset "Master2.rda"
data("Master2")

## Normalize spectrum "Before1" using the RMS method
ex <- normSpectra(dat = Master2, mass_dat = "full_mz", method = "RMS", spectra_cols = "Before1")