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seqinr (version 3.1-2)

stutterabif: Stutter ratio estimation

Description

This function tries to estimate the stutter ratio, either in terms of peak heigth ratios or peak surface ratio.

Usage

stutterabif(abifdata, chanel, poswild, datapointbefore = 70,
 datapointafter = 20, datapointsigma = 3.5,
 chanel.names = c(1:4, 105), DATA = paste("DATA", chanel.names[chanel], sep = "."),
 maxrfu = 1000, method = "monoH.FC", pms = 6, fig = FALSE)

Arguments

abifdata
the result returned by read.abif
chanel
the dye number
poswild
the position in datapoint units of the allele at the origin of the stutter product, typically obtained after a call to peakabif
datapointbefore
how many datapoints before poswild to be include in analysis
datapointafter
how many datapoints after poswild to be include in analysis
datapointsigma
initial guess for the standard deviation of a peak
chanel.names
numbers extensions used for the DATA
DATA
names of the DATA components
maxrfu
argument passed to baselineabif
method
method to be used by splinefun
pms
how many standard deviations (after gaussian fit) before and after the mean peak values should be considered for spline function interpolation
fig
should a summary plot be produced?

Value

  • A list with the following components:
  • rhStutter ratio computed as the height of the stutter divided by the height of its corresponding allele
  • rsStutter ratio computed as the surface of the stutter divided by the surface of its corresponding allele
  • h1The height of the stutter with baseline at 0
  • h2The height of the allele with baseline at 0
  • s1The surface of the stutter
  • s2The surface of the allele
  • pA list of additional parameter that could be usesfull, see example

Details

FIXME, See R code for now

See Also

JLO for a dataset example, peakabif to get an estimate of peak location.

Examples

Run this code
#
  # Load pre-defined dataset, same as what would be obtained with read.abif:
  #

data(JLO)

  #
  # Get peak locations in the blue channel:
  #

maxis <- peakabif(JLO, 1, npeak = 6, tmin = 3, fig = FALSE)$maxis

  #
  # Compute stutter ratio for first peak and ask for a figure:
  #

tmp <- stutterabif(JLO, 1, maxis[1], fig = TRUE)

  #
  # Show in addition the normal approximation used at the stutter peak:
  #

xx <- seq(tmp$p$mu1 - 6*tmp$p$sd1, tmp$p$mu1 + 6*tmp$p$sd1, le = 100)
lines(xx, tmp$p$p1*dnorm(xx, tmp$p$mu1, tmp$p$sd1), col = "darkgreen")

  #
  # Show in addition the normal approximation used at allele peak:
  #

xx <- seq(tmp$p$mu2 - 6*tmp$p$sd2, tmp$p$mu2 + 6*tmp$p$sd2, le = 100)
lines(xx, tmp$p$p2*dnorm(xx, tmp$p$mu2, tmp$p$sd2), col = "darkgreen")

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