seqinr (version 3.6-1)

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:

rh

Stutter ratio computed as the height of the stutter divided by the height of its corresponding allele

rs

Stutter ratio computed as the surface of the stutter divided by the surface of its corresponding allele

h1

The height of the stutter with baseline at 0

h2

The height of the allele with baseline at 0

s1

The surface of the stutter

s2

The surface of the allele

p

A 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

# NOT RUN {
  #
  # 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")
# }