PCA: PCA class
In NOISeq: Exploratory analysis and differential expression for RNA-seq data

Description Usage Arguments Slots/List Components Methods Author(s)

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.

## 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 `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.

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

NOISeq documentation built on Nov. 8, 2020, 5:10 p.m.