plot: Plot Method for mbac
In ConesaLab/MultiBaC: Multiomic Batch effect Correction

Description Usage Arguments Details Value Examples

plot function for mbac class.

## S3 method for class 'mbac'
plot(x, y = NULL, typeP = "def", col.by.batch = TRUE,
  col.per.group = NULL, comp2plot = c(1, 2), legend.text = NULL,
  args.legend = NULL, ...)

`x`	mbac object generated by createMbac, ARSyNbac or MultiBaC.
`y`	Currently not used.
`typeP`	type of plot showed. See details.
`col.by.batch`	Argument for PCA plots. TRUE or FALSE. If TRUE (default), samples are colored according to the batch factor. If FALSE, samples are colored according to the experimental conditions.
`col.per.group`	Argument for PCA plots. Color for each group (given by batches or experimental conditions). If NULL (default), the colors are taken from a predefined pallete.
`comp2plot`	Argument for PCA or InnerRel plot. It indicates which components are to be plotted. The default is c(1,2), which means that, in PCA plots, component 1 is plotted in "x" axis and component 2 in "y" axis, and for InnerRel plots, the inner relation plots of components 1 and 2 are to be shown. If more components are indicated, the function will return as many plots as needed to show all the components.
`legend.text`	A vector of text used to construct a legend for the plot. Argument for PCA plot. If NULL (default) batch or conditions names included in the mbac object are used.
`args.legend`	list of additional arguments to pass to legend(); names of the list are used as argument names. Only used if legend.text is supplied.
`...`	Other graphical arguments.

typeP options are: "def" (default option, "Q2 plot" and "Explained variance plot" in case of MultiBaC and "Explained variance plot" in case of ARSyNbac outputs), "inner" (inner correlation plots for each PLS model acroos the components for MultiBaC output), "pca.org" (PCA plot of original data for MultiBaC or ARSyNbac outputs), "pca.cor" (PCA plot of corrected data for MultiBaC or ARSyNbac outputs), "pca.both" (PCA plots for both original and corrected data for MultiBaC or ARSyNbac outputs), and "batch" ("Batch effect estimation" plot for all the output). Remember that PCA plots can only be generated when all the omics share the same variable space (e.g. gene identifiers are provided as names of variables for all data matrices). While the *plot* function can generate all the plot types described above, each plot can also be independently generated by its corresponding function: *Q2_plot (mbac)*, *explained_varPlot (mbac)*, *plot_pca (mbac, typeP = c("pca.org", "pca.cor", "pca.both"), col.by.batch, col.per.group, comp2plot, legend.text, args.legend)*, *batchEstPlot (mbac, commonOmic)*, or *inner_relPlot (mbac, comp2plot = c(1,2))*.

A plot is displayed.

data('multiyeast')

my_mbac <- createMbac (inputOmics = list(A.rna, A.gro, B.rna, B.ribo, C.rna, C.par),
                       batchFactor = c("A", "A", "B", "B", "C", "C"),
                       experimentalDesign = list("A" =  c("Glu+", "Glu+",
                       "Glu+", "Glu-", "Glu-", "Glu-"),
                       "B" = c("Glu+", "Glu+", "Glu-", "Glu-"),
                       "C" = c("Glu+", "Glu+", "Glu-", "Glu-")),
                       omicNames = c("RNA", "GRO", "RNA", "RIBO", "RNA", "PAR"))

my_final_mbac <- MultiBaC (my_mbac,
                           test.comp = NULL, scale = FALSE,
                           center = TRUE, crossval = NULL,
                           Variability = 0.90,
                           Interaction = TRUE ,
                           showplot = FALSE,
                           showinfo = FALSE)
plot(my_final_mbac)