PCA class generated from dat() function with type="PCA". This object contains the results of the PCA on the data matrix as well as the arguments used.

1 2 3 4 | ```
## S4 method for signature 'PCA'
explo.plot(object, samples = 1:2, plottype = "scores", factor = NULL)
## S4 method for signature 'PCA'
dat2save(object)
``` |

`object` |
Object generated from |

`samples` |
Principal components to be plotted. If NULL, the two first components are plotted. |

`plottype` |
If plottype="scores", the experimental samples are displayed in the plot and colored according to the values of the selected factor. If plottype="loadings", the genes are plotted. |

`factor` |
The samples in the score plot will be colored according to the values of the selected factor. If NULL, the first factor is chosen. |

An object of this class contains an element (dat) which is a list with the following components:

`result`

: List containing the output of PCA. It contains the following elements: "eigen" (eigenvalues and eigenvectors from the PCA decomposition),
"var.exp" (variance explained by each Principal Component), "scores" (coefficients of samples in each PC), "loadings" (coefficients of genes in each PC).

`factors`

: Data.frame with factors inherited from object generated by readData() function.

`norm`

: Value provided for argument "norm".

`logtransf`

: Value provided for argument "logtransf".

This class has an specific `show`

method in order to work and print
a summary of the elements which are contained and a `dat2save`

method
to save the relevant information in an object cleanly. It also has an
`explo.plot`

method to plot the data contained in the object.

Sonia Tarazona

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