plot_pca: PCA scatter plot

In antonvsdata/notame: Workflow for non-targeted LC-MS metabolic profiling

PCA scatter plot

Description

Computes PCA using one of the methods provided in the Bioconductor package pcaMethods and plots the two first principal components CITATION: When using this function, cite the pcaMethods package

Usage

plot_pca(
  object,
  pcs = c(1, 2),
  all_features = FALSE,
  center = TRUE,
  scale = "uv",
  color = group_col(object),
  shape = color,
  label = NULL,
  density = FALSE,
  title = "PCA",
  subtitle = NULL,
  color_scale = NA,
  shape_scale = getOption("notame.shape_scale"),
  fill_scale = getOption("notame.fill_scale_dis"),
  text_base_size = 14,
  point_size = 2,
  ...
)

Arguments

object	a MetaboSet object
pcs	numeric vector of length 2, the principal components to plot
all_features	logical, should all features be used? If FALSE (the default), flagged features are removed before visualization.
center	logical, should the data be centered prior to PCA? (usually yes)
scale	scaling used, as in pcaMethods::prep. Default is "uv" for unit variance
color	character, name of the column used for coloring the points. Set to NULL for black color.
shape	character, name of the column used for shape. Set to NULL for uniform round shapes.
label	character, name of the column used for point labels
density	logical, whether to include density plots to both axes. The density curves will be split and colored by the 'color' variable.
title, subtitle	the titles of the plot
color_scale	the color scale as returned by a ggplot function. Set to NA to choose the appropriate scale based on the class of the coloring variable.
shape_scale	the shape scale as returned by a ggplot function
fill_scale	the fill scale used for density curves. If a continuous variable is used as color, density curve will be colorless.
text_base_size	numeric, base size for text
point_size	numeric, size of the points
...	additional arguments passed to pcaMethods::pca

Value

a ggplot object. If density is TRUE, the plot will consist of multiple parts and is harder to modify.

See Also

pca

Examples

plot_pca(merged_sample, color = "Injection_order", shape = "Group")

antonvsdata/notame documentation built on Sept. 14, 2024, 11:09 p.m.