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Threshold estimation for peak detection

Source: R/nmr_baseline_threshold.R
nmr_baseline_threshold.Rd

Estimates the threshold value for peak detection on an nmr_dataset_1D object by examining a range without peaks that you must provide (there is no ppm range guaranteed to be free of peaks for every sample type).

Usage

nmr_baseline_threshold(
  nmr_dataset,
  range_without_peaks = NULL,
  method = c("mean3sd", "median3mad")
)

Arguments

nmr_dataset

An nmr_dataset_1D.

range_without_peaks

A vector with two doubles describing a range without peaks suitable for baseline detection. There is no such a range that works for every sample type, so you must inspect your spectra and provide one.

method

Either "mean3sd" or the more robust "median3mad". See the details.

Value

Numerical. A threshold value in intensity below that no peak is detected.

Details

Two methods can be used:

  • "mean3sd": The mean3sd method computes the mean and the standard deviation of each spectrum in the given range. The mean spectrum and the mean standard deviation are both vectors of length equal to the number of points in the given range. The mean of the mean spectrum the noise. The threshold is defined as center + 3 dispersion, and it is one single threshold for the whole dataset. This is the default for backwards compatibility.

  • "median3mad": First we take the data matrix. If we have estimated a baseline already, subtract it. In the defined region without peaks, estimate the median of each sample and its median absolute deviation. Return a vector of length equal to the number of samples with the median+3mad for each sample. This is a new more robust method.

See also

Other peak detection functions: Pipelines, nmr_detect_peaks(), nmr_detect_peaks_plot(), nmr_detect_peaks_plot_overview(), nmr_detect_peaks_tune_snr(), nmr_identify_regions_blood(), nmr_identify_regions_cell(), nmr_identify_regions_urine(), nmr_integrate_regions()

Examples

ppm_axis <- seq(from = 0, to = 10, length.out = 1000)
data_1r <- matrix(runif(1000, 0, 10), nrow = 1) + 100
dataset_1D <- new_nmr_dataset_1D(
    ppm_axis = ppm_axis,
    data_1r = data_1r,
    metadata = list(external=data.frame(NMRExperiment = "10"))
)
bl_threshold <- nmr_baseline_threshold(dataset_1D, range_without_peaks = c(9.5,10))