R/nmr_baseline_threshold.R
nmr_baseline_threshold.RdEstimates the threshold value for peak detection on an nmr_dataset_1D object by examining a range without peaks, by default the 9.5 - 10 ppm range.
An nmr_dataset_1D.
A vector with two doubles describing a range without peaks suitable for baseline detection
Either "mean3sd" or the more robust "median3mad". See the details.
Numerical. A threshold value in intensity below that no peak is detected.
Two methods can be used:
"mean3sd": The mean3sd method computes the mean and the standard deviation of each spectrum
in the 9.5 - 10 ppm 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.
Other peak detection functions:
Pipelines,
nmr_detect_peaks_plot_overview(),
nmr_detect_peaks_plot(),
nmr_detect_peaks_tune_snr(),
nmr_detect_peaks(),
nmr_identify_regions_blood(),
nmr_identify_regions_cell(),
nmr_identify_regions_urine(),
nmr_integrate_regions()
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))