pcapheno: Principal Component Analysis with Horn's Parallel Analysis
In changebio/MAGPA: Multivariate Analysis of Genotype–Phenotype Association and Visualization for 3D Image
Description
Usage
Arguments
Value
Examples
Description
the function is implemented to automatically extract the principal components from
high-dimension data, which calls paran to performs Horn's parallel analysis
for evaluating the components retained in a principle component analysis.
Usage
1
Arguments
pheno
A matrix with n rows of sample and m columns of features
iterations
sets the number of iterations with a user specified whole number representing
the number of random data sets to be produced in the analysis. The default is 100.
Value
a list of objects with the pca of phenotypes and the results of parallel analysis
Examples
1
2
changebio/MAGPA documentation built on June 15, 2020, 9:26 p.m.
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Description Usage Arguments Value Examples
Description
the function is implemented to automatically extract the principal components from
high-dimension data, which calls paran to performs Horn's parallel analysis
for evaluating the components retained in a principle component analysis.
Usage
1 |
Arguments
pheno |
A matrix with n rows of sample and m columns of features |
iterations |
sets the number of iterations with a user specified whole number representing the number of random data sets to be produced in the analysis. The default is 100. |
Value
a list of objects with the pca of phenotypes and the results of parallel analysis
Examples
1 2 |
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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