Hi,
I am currently analysis Raman spectroscopic data with the hyperSpec package.
I consulted the documentation on this package and I found an example
work-flow dedicated to Raman spectroscopy (see the address :
http://hyperspec.r-forge.r-project.org/chondro.pdf)
I am currently trying to remove outliers thanks to PCA just as they did in
the documentation, but I get a message error I can't explain. Here is my
code :
"#import the data :
T=read.table('bladder bis concatenation colonne.txt',header=TRUE)
spec=new("hyperSpec",wavelength=T[,1],spc=t(T[,-1]),data=data.frame(sample=colnames(T[,-1])),label=list(.wavelength="Raman
shift (cm-1)",spc="Intensity (a.u.)"))
#baseline correction of the spectra
spec=spec[,,500~1800]
bl=spc.fit.poly.below(spec)
spec=spec-bl
#normalization of the spectra
spec=sweep(spec,1,apply(spec,1,mean),'/')
#PCA
pca=prcomp(~ spc,data=spec$.,center=TRUE)
scores=decomposition(spec,pca$x,label.wavelength="PC",label.spc="score/a.u.")
loadings=decomposition(spec,t(pca$rotation),scores=FALSE,label.spc="laoding
I/a.u.")
#plot the scores of the first 20 PC against all other to have an idea where
to find the outliers
pairs(scores[[,,1:20]],pch=19,cex=0.5)
#identify the outliers thanks to "map.identify"
out=map.identify(scores[,,5])
Erreur dans `[.data.frame`(x@data, , j, drop = FALSE) :
undefined columns selected
Does anybody understand where the problem comes from ?
And does anybody know another mean to find spectra outliers ?
Thank you in advance.
Boule
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