msQuantify {msProcess} | R Documentation |
Given an msSet
object containing a
peak.class
element defining a
common set of peak classes,
this function returns either (i) a matrix of peak
intensities or (ii) a count of the peaks that are associated
with each peak class. The measure
argument
is used to specify the output type.
msQuantify(x, xnew=NULL, measure="intensity")
x |
An object of class msSet containing a peak.class element. |
measure |
A character string specifying the measure to be used for quantification.
Choices are
Default: "intensity" . |
xnew |
An object of class msSet .
This object may contain a set of spectra that were not used to originally generate
the peak classes. If the user wishes to quantify the original spectra, set
xnew=NULL . Default: NULL . |
The same input msSet
object (x
if xnew=NULL
, xnew
otherwise)
with an updated/new peak.matrix
element. The rows and columns
of the peak.matrix
are the peak class measures
and peak classes, respectively.
If measure="count"
, the element "peak.list"
is also
updated with a class ID for each peak.
Morris, J.S., Coombes, K.R., Koomen, J., Baggerly, K.A., Kobayashi, R., ``Feature extraction and quantification for mass spectrometry in biomedical applications using the mean spectrum," Bioinformatics, 21(9):1764–75, 2005.
Tibshirani, R., Hastie, T., Narasimhan, B., Soltys, S., Shi, G., Koong, A., and Le, Q.T., ``Sample classification from protein mass spectrometry, by peak probability contrasts," Bioinformatics, 20(17):3034–44, 2004.
Yasui, Y., McLerran, D., Adam, B.L., Winget, M., Thornquist, M., Feng, Z., ``An automated peak identification/calibration procedure for high-dimensional protein measures from mass spectrometers," Journal of Biomedicine and Biotechnology, 2003(4):242–8, 2003.
Yasui, Y., Pepe, M., Thompson, M.L., Adam, B.L., Wright, Jr., G.L., Qu, Y., Potter, J.D., Winget, M., Thornquist, M., and Feng, Z., ``A data-analytic strategy for protein biomarker discovery: Profiling of high-dimensional proteomic data for cancer detection," Biostatistics, 4(3):449–63, 2003.
msQuantifyIntensity
, msQuantifyCount
, msAlign
.
if (!exists("qcset")) data("qcset", package="msProcess") ## extract several spectra from the build-in ## dataset z <- qcset[, 1:8] ## denoising z <- msDenoise(z, FUN="wavelet", n.level=10, thresh.scale=2) ## local noise estimation z <- msNoise(z, FUN="mean") ## baseline subtraction z <- msDetrend(z, FUN="monotone", attach=TRUE) ## intensity normalization z <- msNormalize(z) ## peak detection z <- msPeak(z, FUN="simple", use.mean=FALSE, snr=2) ## peak alignment z <- msAlign(z, FUN="cluster", snr.thresh=10, mz.precision=0.004) ## peak quantification using intensity z <- msQuantify(z, measure="intensity") ## extract peak.matrix z[["peak.matrix"]] ## visualize the peak.matrix image(z, what="peak.matrix")