smoothDWT: smooth (denoise) the spectrum by DWT (Discrete Wavelet...

In zeehio/MassSpecWavelet: Peak Detection for Mass Spectrometry data using wavelet-based algorithms

smooth (denoise) the spectrum by DWT (Discrete Wavelet Transform)

Description

Smooth (denoise) the spectrum by DWT (Discrete Wavelet Transform)

Usage

smoothDWT(
  ms,
  nLevel = 6,
  wf = "la8",
  localNoiseTh = seq(1, 0, by = -0.2),
  localWinSize = 500,
  globalNoiseTh = 0.75,
  smoothMethod = c("soft", "hard"),
  method = c("dwt", "modwt")
)

Arguments

ms	a vector representing the mass spectrum
nLevel	the level of DWT decomposition
wf	the name of wavelet for DWT
localNoiseTh	local noise level threshold
localWinSize	local window size for estimate local noise threshold
globalNoiseTh	global noise level threshold
smoothMethod	the method used for denoising. 'hard' means keeping the dwt coefficients higher than the threshold unchanged; "soft" means the dwt coefficients higher than the threshold were subtracted by the threshold.
method	'dwt' or 'modwt' used for decomposition

Value

return the smoothed mass spectrum with the 'detail' component of DWT as an attribute 'detail'.

Author(s)

Pan Du

zeehio/MassSpecWavelet documentation built on May 6, 2023, 1:32 a.m.