scaling: Function to scale metabolomic spectral data.
In MetabolAnalyze: Probabilistic Latent Variable Models for Metabolomic Data
Description
Usage
Arguments
Details
Value
Author(s)
References
Description
This function provides the options of Pareto scaling, unit scaling or no scaling of metabolomic data.
Usage
1
Arguments
Y
An N x p matrix of metabolomic spectra. Each row of Y is an observation's spectrum.
type
Default is "none" meaning the data are not altered. If "pareto", the data are Pareto scaled. If "unit", the data are unit scaled.
Details
Pareto scaling, frequently utilised in metabolomic analyses, scales data by dividing each variable by the square root of the standard deviation. Unit scaling divides each variable by the standard deviation so that each variable has variance equal to 1.
Value
The function returns the requested scaled version of the input matrix Y.
Author(s)
Nyamundanda Gift, Isobel Claire Gormley and Lorraine Brennan.
References
van den Berg, R.A., Hoefsloot, H.C.J, Westerhuis, J.A. and Smilde, A.K. and van der Werf, M.J. (2006) Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics, 7, 1, 142.
Nyamundanda G., Gormley, I.C. and Brennan, L. (2010) Probabilistic principal components analysis for metabolomic data. Technical report, University College Dublin.
MetabolAnalyze documentation built on Aug. 31, 2019, 5:05 p.m.
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Description Usage Arguments Details Value Author(s) References
Description
This function provides the options of Pareto scaling, unit scaling or no scaling of metabolomic data.
Usage
1 |
Arguments
Y |
An N x p matrix of metabolomic spectra. Each row of Y is an observation's spectrum. |
type |
Default is "none" meaning the data are not altered. If "pareto", the data are Pareto scaled. If "unit", the data are unit scaled. |
Details
Pareto scaling, frequently utilised in metabolomic analyses, scales data by dividing each variable by the square root of the standard deviation. Unit scaling divides each variable by the standard deviation so that each variable has variance equal to 1.
Value
The function returns the requested scaled version of the input matrix Y.
Author(s)
Nyamundanda Gift, Isobel Claire Gormley and Lorraine Brennan.
References
van den Berg, R.A., Hoefsloot, H.C.J, Westerhuis, J.A. and Smilde, A.K. and van der Werf, M.J. (2006) Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics, 7, 1, 142.
Nyamundanda G., Gormley, I.C. and Brennan, L. (2010) Probabilistic principal components analysis for metabolomic data. Technical report, University College Dublin.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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