pVCA: Principal variance component analysis.
In gc5k/ProQC: Quality control for proteomics
Description
Principal variance component analysis.
Usage
1
pVCA(pEg, pc=5, Cat)
Arguments
pEg
pEg is the result of eigen analysis.
pc
The number of the eigenvectors used for analysis.
Cat
The variable for analysis. If it is a continous variable, linear regression is used. If it is a categorical variable, ANOVA is used to determine Rsq.
gc5k/ProQC documentation built on March 8, 2020, 8:25 a.m.
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Description
Principal variance component analysis.
Usage
1 | pVCA(pEg, pc=5, Cat)
|
Arguments
pEg |
pEg is the result of eigen analysis. |
pc |
The number of the eigenvectors used for analysis. |
Cat |
The variable for analysis. If it is a continous variable, linear regression is used. If it is a categorical variable, ANOVA is used to determine Rsq. |
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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