plot_pca_genes: Make a PC plot describing the gene' clustering.

In elsayed-lab/hpgltools: A pile of (hopefully) useful R functions

Make a PC plot describing the gene' clustering.

Description

Make a PC plot describing the gene' clustering.

Usage

plot_pca_genes(
  data,
  design = NULL,
  plot_colors = NULL,
  plot_title = NULL,
  plot_size = 2,
  plot_alpha = 0.4,
  plot_labels = FALSE,
  size_column = NULL,
  pc_method = "fast_svd",
  x_pc = 1,
  y_pc = 2,
  label_column = "description",
  num_pc = 2,
  expt_names = NULL,
  label_chars = 10,
  ...
)

Arguments

data	an expt set of samples.
design	a design matrix and.
plot_colors	a color scheme.
plot_title	a title for the plot.
plot_size	size for the glyphs on the plot.
plot_alpha	Add an alpha channel to the dots?
plot_labels	add labels? Also, what type? FALSE, "default", or "fancy".
size_column	use an experimental factor to size the glyphs of the plot
pc_method	how to extract the components? (svd
x_pc	Component to put on the x axis.
y_pc	Component to put on the y axis.
label_column	Which metadata column to use for labels.
num_pc	How many components to calculate, default to the number of rows in the metadata.
expt_names	Column or character list of preferred sample names.
label_chars	Maximum number of characters before abbreviating sample names.
...	Arguments passed through to the pca implementations and plotter.

Value

a list containing the following (this is currently wrong)

1. pca = the result of fast.svd()

2. plot = ggplot2 pca_plot describing the principle component analysis of the samples.

3. table = a table of the PCA plot data

4. res = a table of the PCA res data

5. variance = a table of the PCA plot variance

See Also

[plot_pcs()]

Examples

## Not run: 
 pca_plot <- plot_pca(expt = expt)
 pca_plot

## End(Not run)

elsayed-lab/hpgltools documentation built on May 9, 2024, 5:02 a.m.