R_MM_backup/noise.est.R

In kimsche/MetaboMate: All you need for NMR-based metabolic profiling with R!

#' Estimation of noise level
#' @export
#' @param NMR Input matrix with rows representing spectra.
#' @param ppm ppm vector with its length equals to \code{ncol(X)}.
#' @param where Signal free region across all NMR spectra (see Details).
#' @details Estimation of noise level in NMR spectra. This is useful for quality control checks (e.g., before and after spectral normalisation). Noise estimation requires a signal-free ppm region across all spectra, usually this is at the extreme ends or the spectrum. This function requires a minimum number of 50 data points to robustly estimate noise levels.
#' @return Returned is a vector of noise levels for each spectrum.
#' @seealso \code{\link{readBruker}}
#' @author Torben Kimhofer \email{tkimhofer@@gmail.com}
#' @importFrom ptw asysm

noise.est=function(NMR, ppm, where=c(14.6,14.7)){

  # set ppm range where noise should be estimated, i.e., no signals
  idx=get.idx(where,ppm)
  if(length(idx)<50){stop("No or too few data points for noise estimation!")}

  noise=apply(NMR[,idx], 1, function(x){
    x_driftcorrected=x-asysm(x, lambda=1e10)
    noi=(max(x_driftcorrected)-min(x_driftcorrected))
    return(noi)
  })
  return(noise)
}