IDPmisc (version 1.1.19)

peaks: Finding Peaks in Raw Data

Description

Returns position, signal height and approximate width at half maximum peak height.

Usage

peaks(x, y = NULL, minPH, minPW, thr, stepF = 0.49)

Arguments

x, y

Position and height of signal. Any reasonable way of defining the coordinates is acceptable. See function link{getXY} for details.

minPH

Mimimum height of peak to be reported.

minPW

Minimum width of peak at half maximum to be reported.

thr

Threshold below which the signal is not processed.

stepF

StepF defines indirectly the accuracy of the selection criteria minPH and minPW and of the value of the calculated width: The smaller the more accurate and the slower the function. It must be <0.5

Value

dataframe consisting of

x

Position of peak

y

Signal height

w

Approximate width at half maximum of peak

Details

The function is especially useful for signals in which both very broad and very narrow peaks are of interest. The peaks may lie very close to each other or might even be superpositioned on top of each other, e.g. peaks on broader shoulders. The algorithm is also very useful when the resolution of the signal is poor and the noise is small.

The function is looking for peaks without any preceding baseline substraction or smoothing, which could distort the spectrum.

The selection criteria minPH and minPW and the values for the calculated peak widths are only approximate.

Examples

# NOT RUN {
n <- 200
freq <- 1:n
theory <- sin(freq/n*4*pi)*cos(freq/n*3*pi)
spec <- theory + 0.1*rnorm(n)

plot(spec,type="b")
lines(theory,lwd=2)

pts <- peaks(spec, minPH=0.7)
points(pts,col="red",cex=1.2, pch=20)

## peaks after smoothing the spectrum
spec.sm <- loess.smooth(freq, spec, span=0.2,
                        degree = 2, evaluation = 100)
lines(spec.sm$x, spec.sm$y, col="steelblue", lwd=2)
pts <- peaks(spec.sm, minPH=0.4)
points(pts,col="green",cex=1.2,pch=20)

## Analyses of Mass Spectrum between 12000 and 100'000
## without smoothing, without baseline substraction
data(MS)
MS1 <- log10(MS[MS$mz>12000&MS$mz<1e5,])

P <- peaks(MS1, minPH=0.02, minPW=0.001)
plot(MS1, type="l", xlab="log10(mz)", ylab="log10(I)")
points(P,col="blue",cex=1.6)

# }