plot_pca: PCA scatter plot

In antonvsdata/amp: Smoothing Metabolomics Analyses

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, all_features = FALSE, center = TRUE, scale = "uv",
  color = group_col(object), shape = NULL, label = NULL,
  density = FALSE, title = "PCA", subtitle = NULL,
  color_scale = NULL, shape_scale = NULL, fill_scale = NULL, ...)

Arguments

object	a MetaboSet object
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
shape	character, name of the column used for shape
label	character, name of the column used for point labels
density	logical, whether to include density plots to both axes
title, subtitle	the titles of the plot
color_scale	the color scale as returned by a ggplot function
shape_scale	the shape scale as returned by a ggplot function
fill_scale	the fill scale used for density curves
...	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/amp documentation built on Jan. 8, 2020, 3:15 a.m.