multiple_pca_plot: Plots multiple components of a PCA
In hipathia: HiPathia: High-throughput Pathway Analysis

Description Usage Arguments Value Examples

Plots multiple components of a PCA analysis computed with do_pca

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multiple_pca_plot(fit, group = NULL, sample_colors = NULL,
  comps = seq_len(3), plot_variance = FALSE, legend = TRUE,
  cex = 2, pch = 20, main = "Multiple PCA plot", save_png = NULL)

`fit`	princomp object as returned by `do_pca`
`group`	Vector with the group to which each sample belongs. The samples must be ordered as in `path_vals`. By default, all samples will be assigned to the same class.
`sample_colors`	Named character vector of colors. The names of the colors must be the classes in `group`. Each sample will be assigned the color corresponding to its class, taken from the `group` vector. By default a color will be assigned automatically to each class.
`comps`	Vector with the components to be plot
`plot_variance`	Logical, whether to plot the cumulative variance.
`legend`	Boolean, whether to plot a legend in the plot. Default is TRUE.
`cex`	Graphical parameter from `par()` function.
`pch`	Graphical parameter from `par()` function.
`main`	Main title of the image
`save_png`	Path to the file where the image as PNG will be saved. By default, the image is not saved.

Plots multiple components of a PCA

data(path_vals)
sample_group <- brca_design[colnames(path_vals),"group"]
pca_model <- do_pca(path_vals[seq_len(ncol(path_vals)),])
multiple_pca_plot(pca_model, sample_group, cex = 3, plot_variance = TRUE)