apply.pca: Applies to the data a principal component analysis
In CNVtools: A package to test genetic association with CNV data
Description
Usage
Arguments
Value
Note
Author(s)
See Also
Description
A simple wrapper around the R function prcomp.
Usage
1
apply.pca(matrix.signal)
Arguments
matrix.signal
A matrix containing the raw calls. The rows are
the samples and the columns are the SNPs.
Value
A one dimensional vector, one value per sample: this is the first
principal component.
Note
The output vector is normalized to have a standard deviation of 1.
Author(s)
Vincent Plagnol vincent.plagnol@cimr.cam.ac.uk and Chris Barnes christopher.barnes@imperial.ac.uk
See Also
prcomp
CNVtools documentation built on April 28, 2020, 6:06 p.m.
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Description Usage Arguments Value Note Author(s) See Also
Description
A simple wrapper around the R function prcomp.
Usage
1 | apply.pca(matrix.signal)
|
Arguments
matrix.signal |
A matrix containing the raw calls. The rows are the samples and the columns are the SNPs. |
Value
A one dimensional vector, one value per sample: this is the first principal component.
Note
The output vector is normalized to have a standard deviation of 1.
Author(s)
Vincent Plagnol vincent.plagnol@cimr.cam.ac.uk and Chris Barnes christopher.barnes@imperial.ac.uk
See Also
prcomp
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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