Simple peak location for data imported with the read.abif
function
using cubic spline interpolation.
peakabif(abifdata,
chanel,
npeak,
thres = 400/yscale,
fig = TRUE,
chanel.names = c(1:4,105),
DATA = paste("DATA", chanel.names[chanel], sep = "."),
tmin = 1/tscale,
tmax = abifdata$Data[["SCAN.1"]]/tscale,
tscale = 1000,
yscale = 1000,
irange = (tmin*tscale):(tmax*tscale),
y = abifdata$Data[[DATA]][irange]/yscale,
method = "monoH.FC",
maxrfu = 1000,
...)
Returns invisibly a list with the unscaled values for the locations of peaks, heights of peaks and surfaces of peaks and baseline estimate. The peak location are in datapoint units, that is an integer starting at 1 for the first experimental point, 2 for the second experimental point, etc. However, due to interpolation between points the estimated peak location is usually not an integer.
the result returned by read.abif
the dye number
the expected number of peaks
scaled threshold value
logical: should localized peaks be plotted
numbers extensions used for the DATA
names of the DATA components
scaled starting time for the time axis
scaled ending time for the time axis
scale factor for the time axis
scale factor for the y-axis (RFU)
indices of data to be plotted
values used for the y-axis
method to be used by splinefun
argument passed to baselineabif
arguments forwarded to plot
J.R. Lobry
citation("seqinr")
function read.abif
to import files in ABIF format,
plotabif
to plot them,
data gs500liz
for internal size standards,
data identifiler
for allele names in the allelic ladder,
data JLO
for an example of an individual sample file,
data ECH
for an example of an allelic lader.
data(JLO)
JLO.maxis <- peakabif(JLO, 5, npeak = 14, tmin = 2.7, thres = 0.1)$maxis
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