plot_pca: plot_pca

Description Usage Arguments Value Examples

View source: R/plot-methods.R

Description

plot_pca

Usage

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plot_pca(mbac, col.by.batch = TRUE, col.per.group = NULL,
  comp2plot = c(1, 2), typeP = "pca.both", legend.text = NULL,
  args.legend = NULL, ...)

Arguments

mbac

Object of class mbac generated by *createMbac*, *ARSyNbac*, *MultiBaC*, *genModelList*, or *batchCorrection*.

col.by.batch

Argument for PCA plots. TRUE or FALSE. If TRUE (default) samples are gruped according to the batch factor. If FALSE samples are gruped according to the experimental desing.

col.per.group

Argument for PCA plot. Indicates the color for each group defined in "groups" argument. If NULL (default) the colors are taken from a predefined pallete.

comp2plot

Indicates which components are plotted. Default is "c(1,2)", which means that component 1 is plotted in "x" axis and component 2 in "y" axis. If more components are indicated, the function will return as many plots as needed to show all the components.

typeP

"pca.cor", "pca.org" or "pca.both". If inputOmics contains original matrices, set "pca.org". However, if inputOmics contains the corrected matrices, set "pca.cor".

legend.text

a vector of text used to construct a legend for the plot.

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.

Value

A PCA plot is displayed.

Examples

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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"))

plot_pca(my_mbac, typeP = "pca.org")

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_pca(my_final_mbac, typeP = "pca.cor")

MultiBaC documentation built on Nov. 8, 2020, 6:07 p.m.