PCA {NOISeq} | R Documentation

## PCA class

### Description

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.

### Usage

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

### Arguments

`object` | Object generated from `dat()` function.
`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.

### Slots/List Components

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".

### Methods

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.

### Author(s)

Sonia Tarazona

[Package NOISeq version 2.38.0 Index]