msQuantifyIntensity: Spectral Peak Intensities Associated with a Peak Class
In zeehio/msProcess: Protein Mass Spectra Processing

Description Usage Arguments Value References See Also

Given an msSet object, this function quantifies the spectral peak intensities associated with a common set of peak classes. The measure used to identify candidate peaks is the maximum intensity value found over a pre-defined span of the corresponding peak class.

1	msQuantifyIntensity(x, xnew=NULL)

`x`	An object of class `msSet` containing the `peak.class` element.
`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.

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.

msQuantify, msQuantifyCount.

zeehio/msProcess documentation built on May 4, 2019, 10:15 p.m.