pca_score_plot: pca_score_plot

In jaspershen/massstat: Statistical analysis for LC-MS-based metabolomics data

pca_score_plot

Description

pca_score_plot

Usage

pca_score_plot(
  object,
  pca_object,
  x = 1,
  y = 2,
  color_by,
  point_alpha = 1,
  point_size = 5,
  point_shape = 21,
  frame = TRUE,
  frame.type = "norm",
  ...
)

Arguments

object	mass_dataset.
pca_object	pca_object from run_pca()
x	PC x for X axis, default is 1.
y	PC y for Y axis, default is 2.
color_by	which column (sample_info) is used to color samples
point_alpha	point_alpha default is 1.
point_size	point_size, default is 5.
point_shape	point_shape default is 21.
frame	?ggplot2::autoplot
frame.type	?ggplot2::autoplot
...	other paramters for ggplot2::autoplot

Value

ggplot2 plot.

Author(s)

Xiaotao Shen [e-mail]

Examples

library(massdataset)
library(magrittr)
library(dplyr)
data("liver_aging_pos")
liver_aging_pos

pca_object =
  liver_aging_pos %>%
  scale() %>%
  run_pca()

pca_score_plot(liver_aging_pos,
               pca_object,
               color_by = "group",
               loadings = TRUE)

pca_score_plot(liver_aging_pos,
               pca_object,
               color_by = "group",
               frame = TRUE) +
  ggrepel::geom_text_repel(aes(label = sample_id))

pca_score_plot(liver_aging_pos,
               pca_object,
               x = 1,
               y = 3,
               color_by = "group",
               frame = TRUE) +
  ggrepel::geom_text_repel(aes(label = sample_id))

jaspershen/massstat documentation built on Sept. 29, 2022, 4:30 a.m.