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Locate bead populations in one channel

Source: R/calibration.R
bead_peaks.Rd

Bead sets are discrete populations, so the peaks of the density are the populations. Peaks are returned in ascending order, which is the order assigned-value tables conventionally use.

Usage

bead_peaks(
  x,
  n_expected,
  bins = 256L,
  smooth = 5,
  min_frac = 0.005,
  min_sep_log10 = 0.15
)

Arguments

x

channel values for the bead file, in linear instrument units

n_expected

how many populations the bead set has

bins, smooth

density resolution and smoothing

min_frac

smallest share of events a population must hold

min_sep_log10

minimum separation between two populations, in decades. Bead populations are narrow, so histogram noise readily splits one of them into two adjacent maxima; without a separation rule the split pair occupies two of the expected slots and the brightest real population is dropped.

Value

numeric vector of peak locations, ascending, or NULL