plot_pca_hexbin: PCA hexbin plot

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

PCA hexbin plot

Description

Computes PCA using one of the methods provided in the Bioconductor package pcaMethods and plots the two first principal components as hexagonal bins, where the value of the coloring variable is summarised for each bin, by default as the mean of the values inside the bin. CITATION: When using this function, cite the pcaMethods package

Usage

plot_pca_hexbin(
  object,
  pcs = c(1, 2),
  all_features = FALSE,
  center = TRUE,
  scale = "uv",
  fill = "Injection_order",
  summary_fun = "mean",
  bins = 10,
  title = "PCA",
  subtitle = NULL,
  fill_scale = getOption("notame.fill_scale_con"),
  ...
)

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
fill	character, name of the column used for coloring the hexagons
summary_fun	the function used to compute the value for each hexagon
bins	the number of bins in x and y axes
title, subtitle	the titles of the plot
fill_scale	the fill scale as returned by a ggplot function
...	additional arguments passed to pcaMethods::pca

Value

A ggplot object.

See Also

pca

Examples

plot_pca_hexbin(merged_sample)

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