Description Usage Arguments Details Value

Applies pemutation method to return the most significant components of PCA data

1 | ```
applyPermutationWPCA(expr, components = 50, p_threshold = 0.05)
``` |

`expr` |
Expression data |

`components` |
Maximum components to calculate. Default is 50. |

`p_threshold` |
P Value to cutoff components at. Default is .05. |

Based on the method proposed by Buja and Eyuboglu (1992), PCA is performed on the data then a permutation procedure is used to assess the significance of components

(list):

wPCA: weighted PCA data

eval: the proortinal variance of each component

evec: the eigenvectors of the covariance matrix

permuteMatrices: the permuted matrices generated as the null distrbution

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